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
Status of Claims
This action is in reply to the communication filed on 05/15/2025.
Claims 1-20 are currently pending and have been examined.
Claim Objections
Claims 1,13 and 16 are objected to because of the following informalities: Claims 1, 13 and 16 recite the term “ AI”. Applicant needs to define what the acronym stands for prior to using it. For example, Applicant can state for short Message Service (SMS) and then use the acronym SMS. Appropriate correction is required.
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 1-20 are directed to a system, and a non -transitory computer readable medium which would be classified under one of the listed statutory classifications (i.e., 2019 Revised Patent Subject Matter Eligibility Guidance (hereinafter “PEG”) “PEG” Step 1=Yes).
However, claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the following abstract idea:
receive, via the communication interface, a customer request from a customer in a store;
generate reply text in response to the customer request, the reply text being generated using a generative algorithm based on a prompt corresponding to the customer request;
supply a customer response to the customer based on the generated reply text;
receive customer behavior information for the customer and track a behavior of the customer in the store after the customer response has been supplied to the customer; and
record, the customer behavior information representing the tracked behavior of the customer in correlation with the customer response supplied to the customer;
The limitations as detailed above, as drafted, falls within the “Certain Method of Organizing Human Activity” grouping of abstract ideas namely commercial or legal interactions because they recite advertising, marketing and sales activities or behaviors because they merely gather data, analyze the data, determine results based on the analysis, generate tailored content based on the results, and transmit the tailored content. Accordingly, the claim recites an abstract idea (i.e. “PEG” Revised Step 2A Prong One=Yes).
This judicial exception is not integrated into a practical application because the claim only recites the additional elements of “ processing apparatus, comprising: a communication interface connectable to a network; a storage unit; a processor and AI “.
The following limitations, if removed from the abstract idea and considered additional elements, merely perform generic computer function of processing, storing, communicating (e.g., transmitting and receiving), and displaying data and, as such, are insignificant extra-solution activities (see MPEP 2016.05(d)(II) and MPEP 2106.05(g)):
receive, via the communication interface, a customer request from a customer in a store;
receive customer behavior information for the customer and track a behavior of the customer in the store after the customer response has been supplied to the customer; and
record, in the storage unit, the customer behavior information representing the tracked behavior of the customer in correlation with the customer response supplied to the customer;
The additional technical elements above are recited at a high-level of generality (i.e., as a generic processor and generic computer components performing a generic computers function of processing, communicating and displaying) such that it amounts to no more than mere instructions to apply the exception using one or more general-purpose computers and generic computer components. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional technical elements above do not integrate the abstract idea/judicial exception into a practical application because it does not impose any meaningful limits on practicing the abstract idea. More specifically, the additional elements fail to include (1) improvements to the functioning of a computer or to any other technology or technical field (see MPEP 2106.05(a)), (2) applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition (see Vanda memo), (3) applying the judicial exception with, or by use of, a particular machine (see MPEP 2106.05(b)), (4) effecting a transformation or reduction of a particular article to a different state or thing (see MPEP 2106.05(c)), or (5) applying or using 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 designed to monopolize the exception (see MPEP 2106.05(e) and Vanda memo).
Rather, the limitations merely add the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on one or more computers, or merely uses computers as a tool to perform an abstract idea (see MPEP 2106.05(f)), or generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)).
Thus, the claim is “directed to” an abstract idea (i.e. “PEG” Revised Step 2A Prong Two=Yes)
When considering Step 2B of the Alice/Mayo test, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims do not amount to significantly more than the abstract idea.
More specifically, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using “ processing apparatus, comprising: a communication interface connectable to a network; a storage unit; a processor and AI to perform the claimed functions amounts to no more than mere instructions to apply the exception using one or more general-purpose computers and one or more generic computer component.
“Generic computer implementation” is insufficient to transform a patent-ineligible abstract idea into a patent-eligible invention (See Affinity Labs, _F.3d_, 120 U.S.P.Q.2d 1201 (Fed. Cir. 2016), citing Alice, 134 S. Ct. at 2352, 2357) and more generally, “simply appending conventional steps specified at a high level of generality” to an abstract idea does not make that idea patentable (See Affinity Labs, _F.3d_, 120 U.S.P.Q.2d 1201 (Fed. Cir. 2016), citing Mayo, 132 S. Ct. at 1300). Moreover, “the use of generic computer elements like a microprocessor or user interface do not alone transform an otherwise abstract idea into patent-eligible subject matter (See FairWarning, 120 U.S.P.Q.2d. 1293, citing DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1256 (Fed. Cir. 2014)). As such, the additional elements of the claim do not add a meaningful limitation to the abstract idea because they would be generic computer functions in any computer implementation. 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 the computer or improves any other technology. Their collective functions merely provide generic computer implementation.
The Examiner notes simply implementing an abstract concept on one or more computers, without meaningful limitations to that concept, does not transform a patent-ineligible claim into a patent-eligible one (See Accenture, 728 F.3d 1336, 108 U.S.P.Q.2d 1173 (Fed. Cir. 2013), citing Bancorp, 687 F.3d at 1280), limiting the application of an abstract idea to one field of use does not necessarily guard against preempting all uses of the abstract idea (See Accenture, 728 F.3d 1336, 108 U.S.P.Q.2d 1173 (Fed. Cir. 2013), citing Bilski, 130 S. Ct. at 3231), and further the prohibition against patenting an abstract principle “cannot be circumvented by attempting to limit the use of the [principle] to a particular technological environment” (See Accenture, 728 F.3d 1336, 108 U.S.P.Q.2d 1173 (Fed. Cir. 2013), citing Flook, 437 U.S. at 584), and finally merely limiting the field of use of the abstract idea to a particular existing technological environment does not render the claims any less abstract (See Affinity Labs, _F.3d_, 120 U.S.P.Q.2d 1201 (Fed. Cir. 2016), citing Alice, 134 S. Ct. at 2358; Mayo, 132 S. Ct. at 1294; Bilski v. Kappos, 561 U.S. 593, 612 (2010); Content Extraction & Transmission LLC v. Wells Fargo Bank, Nat’l Ass’n, 776 F.3d 1343, 1348 (Fed. Cir. 2014); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355 (Fed. Cir. 2014).
Applicant herein only requires one or more general-purpose computer and generic computer components (as evidenced from paragraphs 57 and 117 of the applicant’s specification); therefore, there does not appear to be any alteration or modification to the generic activities indicated, and they are also therefore recognized as insignificant activity with respect to eligibility. Finally, the following limitations, if removed from the abstract idea and considered additional elements, would be considered insignificant extra solution activity as they are directed to merely receiving, displaying, storing, and/or transmitting data (see MPEP 2016.05(d)(II) and MPEP 2106.05(g)):
sending, by a plurality of second wagering servers associated respectively with second wagering venues, calculated odds to a user device (transmitting data);
displaying, by the user device, a stream of a live sporting event to a user (displaying data);
receiving, by the user device, a wager associated with the stream display a stream of a live sporting event the wager associated with a first wagering venue (receiving data);
receiving, by the user device, a plurality of real-time feeds from at least a plurality of the selected second wagering venues, in which each real-time feed indicates respective odds for the wager associated with the stream of the live sporting event (receiving data);
transmitting, by the user device, an indication of the consensus odds to the first wagering venue (transmitting data).
Thus, taken individually and in combination, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea) (i.e., “PEG” Step 2B=No). For the same reason these elements are not sufficient to provide an inventive concept. For these reasons, there is no inventive concept in the claim, and thus the claim is not patent eligible. Same Judicial analysis is applied here to independent claims 13 recite the additional elements of ( system, AI, cameras , network, server, storage unit , communication interface, portable terminal); claim 16 recites the additional elements of ( computer-readable medium storing program instructions which when executed by a processor, server, system, a communication interface and an AI”.
The dependent claims 2-12, 14-15 and 17-20 appear to merely further limit the abstract idea and which is considered part of the abstract idea and therefore only further limit the abstract idea (i.e. MPEP Step 2A Prong One=Yes), does/do not include any new additional elements that are sufficient to amount to significantly more than the judicial exception, and as such are “directed to” said abstract idea (i.e. MPEP Step 2A Prong Two=Yes); and do not add significantly more than the idea (i.e. MPEP Step 2B=No). Thus, the dependent claims further narrows the abstract idea and/or recite additional elements previously rejected in the independent claims 1,13 and 16. Thus, based on the detailed analysis above, claims 1-20 are not patent eligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. § 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Chachek et al, US Pub No :20250029170 A1.
As per claims 1,13, 16, Chachek teaches:
receive, via the communication interface, a customer request from a customer in a store;
generate reply text in response to the customer request, the reply text being generated using a generative AI based on a prompt corresponding to the customer request;
see at least paragraph 63 (A user may be inside the store (or other mapped environment) and may utilize a smartphone (or other portable electronic device) to request assistance with in-store navigation or wayfinding or route guidance. In a first example, the user inputs to his smartphone the query “I am looking right now at the Frosted Flakes shelf; how do I get from here to the Milk?”);
supply a customer response to the customer based on the generated reply text (see at least paragraph 64 (Based on the user's input, the user's electronic device, locally and/or with the assistance of a remote server, may operate as follows: (a) parse the user query to extract from it the desired destination; (b) extract or deduce the precise current in-store location of the user; (c) determine a walking route from the current location to the destination, based on the Store Map and by utilizing a suitable route guidance algorithm; (d) generate turn-by-turn walking instructions for such route, and convey them to the user by voice and/or text and/or animation and/or other means, as a bulk set of instructions, or as a gradually exposed set of instructions that keeps being updated as the user walks);
receive customer behavior information for the customer and track a behavior of the customer in the store after the customer response has been supplied to the customer; and record, in the storage unit, the customer behavior information representing the tracked behavior of the customer in correlation with the customer response supplied to the customer (see at least paragraph 64 (The set of instructions may be tailored or customized by the system, to be based on in-store elements or products, and not necessarily be based only on Aisle numbers; for example, by generating walking instructions of: (i) turn to your left; (ii) walk 30 feet until you see the Poultry section; (iii) turn there to your right; (iv) walk 20 feet until you see the Dairy section; (v) turn there to your left; (vi) walk 6 feet and you reach the Milk, which is located at the lowest shelf (your knee level) within a closed fridge. The routing instructions may thus be based on Products or in-store items or in-store elements, and may optionally include instructions based on Aisle numbers (e.g., “turn left at Aisle 6”); paragraph 65 (the AR-based navigation instructions that are generated, displayed and/or conveyed to the user, may include AR-based arrows or indicators that are shown as an overlay on top of an aisle or shelf of products, which guide the user to walk or move or turn to a particular direction in order to find a particular product; such as, the user stands in front of the Soda shelf, which is a long shelf of 7 meters; he requested to be navigated to Sprite, and he is currently seeing through his device the shelf-portion that stores bottles of Pepsi; the system generates AR-based content, such as an AR-based arrow that points to the left and has a textual label of “walk 3 meters to your left to see Sprite”, and that content is shown on the visualization of the Pepsi shelf on the user device. For example, such AR-based or VR-based navigation arrows or indicators, are shown as an overlay on products, to guide the user how or where to move within the aisle or the category of products in the store);
As per claim 2, 17, Chachek teaches:
wherein the customer behavior information is customer movement information for the customer in the store (see at least paragraph 64 (The set of instructions may be tailored or customized by the system, to be based on in-store elements or products, and not necessarily be based only on Aisle numbers; for example, by generating walking instructions of: (i) turn to your left; (ii) walk 30 feet until you see the Poultry section; (iii) turn there to your right; (iv) walk 20 feet until you see the Dairy section; (v) turn there to your left; (vi) walk 6 feet and you reach the Milk, which is located at the lowest shelf (your knee level) within a closed fridge. The routing instructions may thus be based on Products or in-store items or in-store elements, and may optionally include instructions based on Aisle numbers (e.g., “turn left at Aisle 6”);
As per claims 3, 4, and 14-15,18 Chachek teaches:
wherein the processor receives images of the customer in the store and tracks, based on the received images, movements of the customer in the store to provide the customer behavior information;
an image capturing device in the store, wherein the images of the customer are provided by the image capturing device;
wherein the customer behavior information is customer movement information for the customer in the store provided by analysis of images from the plurality of cameras.
wherein the processor receives images of the customer from the plurality of cameras in the store and tracks, based on the received images, movements of the customer in the store to provide the customer behavior information;
See at least paragraphs 58-60, paragraph 58 ( digital representation of a Store Map 101 is created by a Map Generator unit 102, which may be based on operations performed by a human administrator and/or by automatic or semi-automatic tools or machines (e.g., a 360-degrees camera assembly that is mounted on a travelling robot or travelling vehicle), and/or may be generated based on a crowd-sourced effort of participating end-user devices (e.g., smartphones of customers) that perform imaging of the store and further perform local computer vision analysis of captured images or video streams);
As per claims 5-9, Chachek teaches:
wherein the processor is further configured to generate the prompt by incorporating portions of the received customer request into an instruction to generate text associated with merchandise to be suggested to the customer;
wherein the customer response includes a recommended behavior for the customer in the store;
wherein the processor is further configured to add additional information to the reply text to generate the customer response;
wherein the processor is further configured to change a format of the reply text to generate the customer response;
wherein the processor is further configured to change a format of the reply text to generate the customer response;
see at least paragraph 63 (A user may be inside the store (or other mapped environment) and may utilize a smartphone (or other portable electronic device) to request assistance with in-store navigation or wayfinding or route guidance. In a first example, the user inputs to his smartphone the query “I am looking right now at the Frosted Flakes shelf; how do I get from here to the Milk?”. The input may be provided by typing into the smartphone, or by dictating the query by voice which the smartphone captures and then converts to a textual query (e.g., locally within the smartphone and/or via a cloud-based or remote speech-to-text unit). Optionally, the input may be provided by the user via other means; for example, the user may lift his smartphone to be generally perpendicular to the ground, may take a photo of the Frosted Flakes shelves, and may say “take me to the Milk” or “I need to buy Milk”; and the smartphone or a cloud-based server may perform content analysis of the photo (e.g., via Optical Character Recognition (OCR) and/or via computerized vision or computerized image recognition), and may thus recognize the input-portion indicating that the user is located near (and is facing) the Frosted Flakes and that he desires to go to the Milk shelf or department; paragraph 64 (Based on the user's input, the user's electronic device, locally and/or with the assistance of a remote server, may operate as follows: (a) parse the user query to extract from it the desired destination; (b) extract or deduce the precise current in-store location of the user; (c) determine a walking route from the current location to the destination, based on the Store Map and by utilizing a suitable route guidance algorithm; (d) generate turn-by-turn walking instructions for such route, and convey them to the user by voice and/or text and/or animation and/or other means, as a bulk set of instructions, or as a gradually exposed set of instructions that keeps being updated as the user walks. The set of instructions may be tailored or customized by the system, to be based on in-store elements or products, and not necessarily be based only on Aisle numbers; for example, by generating walking instructions of: (i) turn to your left; (ii) walk 30 feet until you see the Poultry section; (iii) turn there to your right; (iv) walk 20 feet until you see the Dairy section; (v) turn there to your left; (vi) walk 6 feet and you reach the Milk, which is located at the lowest shelf (your knee level) within a closed fridge. The routing instructions may thus be based on Products or in-store items or in-store elements, and may optionally include instructions based on Aisle numbers (e.g., “turn left at Aisle 6”).
As per claims 10,19, Chachek teaches:
compare the recorded behavior information to the customer response to detect whether the customer response caused a behavior change in the customer; and generate an analysis report based on the comparison of the recorded behavior information to the customer response (see at least paragraph 139 (the content displayed in or near the rings of the on-screen compass, may dynamically and automatically change or updated, based on the changing in-store location of the user, and/or based also on the spatial orientation of the user's smartphone (e.g., facing north, or facing south-cast, or the like). For example, as the user makes a left turn from Aisle 4 to Corridor 5, the on-screen compass navigator rotates automatically by 90 degrees, and reveals a new category of items that can now be viewed in real life because of this turn, and/or changes the direction of another category due to that turn (e.g., a previous category of “Dairy Items” used to be ahead or “up”, but due to the left turn of the user in the store, that category is now located on the Right side of the user and thus is shown in the “east” side of the category ring);
As per claim 11, Chachek teaches:
wherein the processor is further configured to change a method of generating the reply text based on the analysis report (see at least paragraph 121(associated with the store map, and may optionally be associated with various meta-data and/or features which may be tracked and monitored and then reported (e.g., how many shoppers have stopped in front of a particular merchandise table in the past 24 hours; how many shoppers have picked up an item from a particular shelf in the past week; or the like);
As per claims 12, 20, Chachek teaches:
wherein the processor is further configured to change a method of presenting the customer response based on the analysis report (see at least paragraph 76 ( navigation routes to an in-venue destination may be modified or generated by the system in order to intentionally include (or preclude) a particular route-segment or venue-segment or venue-region, due to one or more reasons or conditions; for example, dynamically navigating user Adam from Breads to Eggs in a route that avoids Aisle 5 because based on localization of users in the store, Aisle 5 is currently extremely crowded (e.g., has at least 15 persons in that aisle at this time); or in a route that excludes Aisle 3 because the store map has recently been updated by a store employee to indicate that there is a liquid spill on the floor there, or such hazard was automatically detected via sensors and/or imagers of the store (e.g., using computer vision analysis), and/or based on user-submitted reports (e.g., a shopper and/or an employee have reported a hazard in Aisle 3). In another example, the navigation route to a particular in-venue destination may be modified to necessarily include an in-venue area or location or segment that the venue administrator wishes to make more popular, or that includes new products or promoted products; or that a third-party advertiser had paid for inclusion in such in-venue navigation routes. In some embodiments, users in general, or particular types of users (e.g., female visitors; or teenage visitors; or senior citizens; or users that have shopped for Gluten Free items; or the like), may be presented with particularly tailored in-venue navigation routes, to accommodate a pre-defined marketing plan that the venue wishes to implement with regard to this type of users or population; for example, guiding senior citizens towards their in-store destination via Aisle 6 which includes hearing aids and reading glasses, while guiding teenage shoppers towards the same in-store destination via Aisle 9 which includes skateboards and basketballs; thereby tailoring an in-venue or in-store navigation route, towards a desired destination, based on the characteristics of the particular user that is being navigated towards it);
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Boyd et al, US Pub No: 20250371324 A1, teaches Generative Model Experience using open prompt.
Aznauashvili et al US Pub No: 20200005336 A1 teaches systems and methods for pre communicating shoppers communication preferences to retailers.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Affaf Ahmed whose telephone number is 571-270-1835. The examiner can normally be reached on [M- R 8-6 pm ].
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ilana Spar can be reached at 571-270-7537. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/AFAF OSMAN BILAL AHMED/Primary Examiner, Art Unit 3622
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