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 .
Response to Amendment
This Office action is in response to the Amendment filed on 05/10/2026.
Claims 3, 6-8, and 24-25 are canceled.
Claims 28-32 are new.
Claims 10-13, 16, and 20 are withdrawn-currently amended.
Claims 1-2, 4-5, 9, 14-15, 17-19, 21-23, and 26-27 are currently amended.
Claims 1-2, 4-5, 9, 14-15, 17-19, 21-23, and 26-32 are currently pending and addressed below.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-2, 4-5, 9, 14-15, 17-19, 21-23, and 26-32 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 1 and 27-28 recite “automatically generating by said neural network unit an output that depends at least on analysis of content of said one or more images, wherein the analysis includes using the neural network unit to perform non-barcode-based object recognition” and “providing to the electronic device the output generated by said neural network unit to be presented to the user on the display of the electronic device to enable adjustment of product placement and product display inventory based on the image information.”
Claim 2 recites “automatically commanding said neural network unit to generate a response to generate an output including product availability, inventory status, or product condition information based on said one or more images to said request based on said one or more images” and “transmitting to the electronic device from said neural network unit a neural network unit-generated output to be provided to said user via said electronic device.”
Claim 9 recites “receiving at the neural network unit as additional input an inventory map representing planned in-store locations of products that are sold at said retailer venue” and “generating by the neural network unit an output that indicates: a name or an image of a particular product that the neural network unit determined to be currently located on a particular shelf and that should regularly be placed at another location in said retailer venue.”
Claim 14 recites “(ii) an inventory map representing planned in- store locations of products that are sold at said retailer venue,” (iii) a user request for in-store navigation guidance from a current location of said electronic device within said retailer venue to a user-indicated in-store target product,” and “based on neural network unit analysis of the inputs that were received at the neural network unit, determining by the neural network unit which in-store location has the target product that was indicated in said request, and generating by said neural network unit step-by-step or turn-by-turn navigation guidance from the current location of said electronic device within said retailer venue to said in-store location that the neural network unit determined to have said target product.”
Claim 15 recites “receiving by the neural network unit as further input an inventory map representing planned in-store locations of products that are sold at said retailer venue” and “determining by said neural network unit a precise current location of said electronic device within said retailer venue, by performing neural network unit analysis of said one or more images in relation to said inventory map.”
Claim 17 recites “receiving by said neural network unit as inputs at least: (i) a user-provided request to get navigation guidance from the current location of said user to said particular type-of-product in said retailer venue, (ii) an inventory map of said retailer venue that conveys data about planned placement of products on shelves, (iii) location-indicating information that enables the neural network unit to deduce the current location of the electronic device of said user; and based on the inputs that were fed into the neural network unit in step (II), generating by said neural network unit navigation guidance from the current location of the electronic device to an in-store location that is expected to have products that belong to said type-of-product that was indicated in said user-provided request.”
Claim 18 recites “wherein the neural network unit is configured to autonomously estimate whether a particular product that is offered for sale at said retailer venue belongs or does not belong to the particular type-of-product that was conveyed in said user-provided request; and wherein said neural network unit has access to information about product ingredients and product characteristics”
Claim 21 recites “receiving by the neural network unit as further inputs at least (i) an inventory map representing planned in-store locations of products that are sold at said retailer venue, and (ii) a user-provided request to find a real-world in-store location of a product having a particular set of user-defined characteristics; and generating by said neural network unit in-store navigation guidance that leads from a current location of the electronic device to an in-store destination that has a product that the neural network unit determines determined to have said particular set of user-defined characteristics.”
Claim 22 recites “autonomously providing, by said neural network unit, neural network unit-generated responses to real-time inquiries that are received from the electronic device with regard to one or more of said products.”
Claim 23 recites “receiving by the neural network unit, in real time or near real time, one or more queries that said user utters; generating by the neural network unit responses to said queries based at least on neural network unit analysis of content depicted in said real-time video stream; and conveying back to said user, via said electronic device, neural network unit-generated responses to said shopping-related queries, via at least one of: (i) speech-based responses to be audibly output by the electronic device, (ii) on-screen responses to be presented visually on a screen of the electronic device, or (iii) an Augmented Reality (AR) layer or a Mixed Reality layer to be presented to said user via said electronic device.”
Claim 26 recites “wherein the input images contain images obtained by the electronic device that reflect spatial movement and reorientation based on six degrees of freedom (6DoF), and wherein the neural network unit is configured to perform analysis and provide output that accounts for the spatial movement and reorientation based on 6DoF.”
The specification fails to reasonable convey the above limitations being performed or generated by the neural network unit. The Examiner respectfully requests Applicant to point to the exact paragraph(s) of the specification that reasonably convey the neural network unit performing or generating the above limitations. The dependent claim are also rejected based on their dependency.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 30 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claim 30 recites the limitation “at least one further inventor map or planogram with a previously created or updated inventory map or planogram.” The Examiner suggests amending “inventor” to “inventory” to overcome the rejection.
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 1-2, 4-5, 9, 14-15, 17-19, 21-23, and 26-32 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a nature phenomenon, or an abstract idea) without significantly more.
Step 1:
Claims 1-2, 4-5, 9, 14-15, 17-19, 21-23, and 26-32 is/are directed towards a statutory category (i.e., a process, machine, manufacture, or composition of matter) (Step 1, Yes).
Step 2A Prong One:
Claim 1 recites (additional elements underlined):
A method comprising:
(a) receiving by a neural network unit one or more images that are captured within a retailer venue by an image capture device of an electronic device of a user selected from the group consisting of: (i) a smartphone, (ii) an Augmented Reality (AR) device, (iii) smart glasses or smart sunglasses that include at least a camera and a memory unit and a processor;
(b) automatically generating by said neural network unit an output that depends at least on analysis of content of said one or more images, wherein the analysis includes using the neural network unit to perform non-barcode-based object recognition that is refined based on multiple images of a given region based on plural images captured from different angles and stitching together the plural images of the given region, the objects including products and product display spaces in the retailer venue, wherein the object recognition is used to create or update at least one inventory map or planogram, wherein the created or updated at least one inventory map or planogram is compared with at least one predefined inventory map or planogram to obtain respective states of product display spaces, and wherein the output comprises electronic image information about the objects and object display spaces, based on the comparison for presentation on a display of the electronic device;
(c) providing to the electronic device the output generated by said neural network unit to be presented to the user on the display of the electronic device to enable adjustment of product placement and product display inventory based on the image information.
The limitations outlined above describe or set forth a commercial interaction (e.g., advertising, marketing or sales activities or behaviors, business relations). Commercial interactions fall within the certain method of organizing human activity enumerated grouping of abstract ideas. The limitations outlined above also describe or set forth a fundamental economic principle or practice because commercial interactions are related to commerce and economy. The limitations outlined above also describe or set forth the managing of personal behavior or relationships or interactions between people. Therefore, the claim recites a certain method of organizing human activity (Step 2A Prong One, Yes).
The limitations outlined above that describe or set forth the abstract idea, cover performance of the limitations in the mind but for the recitation of generic computer(s) and/or generic computer component(s). That is, other than reciting the additional elements, nothing in the claim precludes the limitations from practically being performed in the mind. These limitations are considered a mental process because the limitations include an observation, evaluation, judgment, and/or opinion. These limitations are also similar to “collecting information, analyzing it, and displaying certain results of the collection and analysis” and/or “collecting and comparing known information” which were determined to be mental processes in MPEP 2106.04(a)(2)(III)(A). The Examiner notes that “[c]laims can recite a mental process even if they are claimed as being performed on a computer” (see MPEP 2106.04(a)(2)(III)(C)). The mere nominal recitation of the additional elements identified above do not take the claims out of the mental process grouping. Therefore, the claim recite a mental process (Step 2A Prong One, Yes).
Step 2A Prong Two:
In Step 2A Prong Two, the additional element(s) outlined above are recited at a high level of generality, and under the broadest reasonable interpretation, are generic computer(s) and/or generic computer component(s) that perform generic computer functions. The additional element(s) are merely used as tools, in their ordinary capacity, to perform the abstract idea. The additional element(s) amount adding the words “apply it” with the judicial exception. Merely implementing an abstract idea on generic computer(s) and/or generic computer component(s) does not integrate the judicial exception similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer. The Examiner notes that “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 pp 10-11 of FairWarning IP, LLC. v. Iatric Systems, Inc. (Fed. Cir. 2016)). The additional elements also amount to generally linking the use of the abstract idea to a particular technological environment or field of use (e.g., in a computer environment). The courts have found that simply limiting the use of the abstract idea to a particular environment does not integrate the judicial exception into a practical application. Viewing the limitations as an ordered combination does not add anything further than looking at the limitations individually. There is no indication that the combination of elements improves the functioning of a computer, improves any other technology or technical field, applies or uses the judicial exception to effect a particular treatment or prophylaxis for disease or medical condition, applies the judicial exception with, or by use of a particular machine, effects a transformation or reduction of a particular article to a different state or thing, or applies or uses 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 claims as a whole is more than a drafting effort designed to monopolize the exception. Their collective functions merely provide generic computer implementation (Step 2A Prong Two, No).
Step 2B:
In Step 2B, the additional elements also do not amount to significantly more for the same reasons set forth with respect to Step 2A Prong Two. The Examiner notes that revised Step 2A Prong Two overlaps with Step 2B, and thus, many of the considerations need not be reevaluated in Step 2B because the answer will be the same. Viewing the limitations as an ordered combination does not add anything further than looking at the limitations individually. Their collective functions merely provide generic computer implementation (Step 2B, No).
Claim(s) 2, 4-5, 9, 14-15, 17-19, 21-23, 26, and 29-31 recite further limitations that also fall within the same abstract ideas identified above with respect to claim 1 (i.e., certain methods of organizing human activities and mental processes).
Claim 2 recites the additional elements “from said electronic device,” “by the neural network unit,” “automatically feeding … into said neural network unit,” “feeding to said neural network unit,” “automatically commanding said neural network unit to,” to the electronic device from said neural network unit a neural network unit,” and “via said electronic device.” Claim 4 recites the additional elements “by said neural network unit” and “that said neural network unit.” Claim 5 recites the additional elements “invoking a Machine Learning (ML),” “by the electronic device,” “ML,” “feeding … into the neural network unit and automatically commanding the neural network unit to,” and “neural network-unit-based.” Claim 9 recites the additional elements “at the neural network unit,” by the neural network unit,” and “that the neural network unit.” Claim 14 recites the additional elements “at the neural network unit,” “by said electronic device,” “of said electronic device,” “neural network unit,” “at the neural network unit,” “by the neural network unit,” “by said neural network unit,” “of said electronic device,” and “that the neural network unit.” Claim 15 recites the additional elements “from said electronic device,” ‘by the neural network unit,” “by said neural network unit,” ‘of said electronic device,” and “neural network unit.” Claim 17 recites the additional elements “by said neural network unit,” “the neural network unit,” “of the electronic device,” “fed into the neural network unit,” “by said neural network unit,” and “of the electronic device.” Claim 18 recites the additional elements “wherein the neural network unit is configured to autonomously” and “wherein said neural network unit.” Claim 19 recites the additional elements “of the electronic device,” “neural network unit-based,” “by the electronic device,” “automatically,” and “on a screen of said electronic device an Augmented Reality (AR) element depicted on-screen.” Claim 21 recites the additional elements “by the neural network unit,” by said neural network unit,” “of the electronic device,” and “the neural network unit.” Claim 22 recites the additional elements “autonomously,” “by said neural network unit,” “neural network unit,” “real-time,” and “from the electronic device.” Claim 23 recites the additional elements “a real-time video stream captured by said electronic device,” “by the neural network unit,” and “in real time or near real time,” “by the neural network unit,” “on neural network unit,” “in said real-time video stream,” “via said electronic device,” “neural network unit,” “by the electronic device,” “on-screen,” “on a screen of the electronic device,” “Augmented Reality (AR) layer or Mixed Reality layer,” and “via said electronic device.” Claim 26 recites the additional elements “by the electronic device that reflects spatial movement and reorientation based on six degrees of freedom (6DoF), and wherein the neural network unit is configured to perform analysis and provide output that accounts for the spatial movement and reorientation based on 6DoF.” Claim 30 recites the additional elements “at the neural network unit” and “automatically.” Claim 31 recites the additional elements “from the electronic device.” However, these additional elements also do not integrate the judicial exception into a practical application or amount to significantly more because they amount to adding the words “apply it” with the judicial exception, mere instructions to implement the idea on a computer, merely using a computer as a tool to perform an abstract idea, and generally linking the use of the judicial exception to a particular technological environment or field of use.
Claims 29 and 32 do not recite any other additional elements. Therefore, for the same reasons explained above with respect to claim 1, claims 29 and 32 also do not integrate the judicial exception into a practical application or amount to significantly more.
Claim 27 recites substantially similar limitations as claim 1. Therefore, for the same reasons explained above with respect to claim 1, claim 27 also recites an abstract idea in Step 2A Prong One (i.e., certain method of organizing human activities and mental processes). Claim 27 recites the additional elements of “A system comprising: one or more hardware processors, that are configured to execute code; wherein the one or more hardware processors are operably associated with one or more memory units that are configured to store code; wherein the one or more hardware processors are configured to implement an analysis unit including a neural network unit configured to,” “by a neural network unit,” “an image capture device of an electronic device,” “selected from the group consisting of (i) a smartphone, (ii) an Augmented Reality (AR) device, (iii) smart glasses or smart sunglasses that include at least a camera and a memory unit and a processor,” “automatically,” “by said neural network unit,” “using the neural network unit,” “electronic,” “on a display of the electronic device,” ‘to the electronic device,” “by said neural network unit,” and “on the display of the electronic device.” However, for the same reasons explained above with respect to claim 1, these additional elements also do not integrate the judicial exception into a practical application or amount to significantly more.
Claim 28 recites substantially similar limitations as claim 1. Therefore, for the same reasons explained above with respect to claim 1, claim 28 also recites an abstract idea in Step 2A Prong One (i.e., certain method of organizing human activities and mental processes). Claim 28 recites the additional elements of “A non-transitory computer-readable medium containing code designed to,” “by a neural network unit,” “an image capture device of an electronic device,” “selected from the group consisting of (i) a smartphone, (ii) an Augmented Reality (AR) device, (iii) smart glasses or smart sunglasses that include at least a camera and a memory unit and a processor,” “automatically,” “by said neural network unit,” “using the neural network unit,” “electronic,” “on a display of the electronic device,” ‘to the electronic device,” “by said neural network unit,” and “on the display of the electronic device.” However, for the same reasons explained above with respect to claim 1, these additional elements also do not integrate the judicial exception into a practical application or amount to significantly more.
Prior Art
After a thorough search on the claims as currently amended, the claims are found to recite novel and non-obvious subject matter. The closest prior art found to date are the following:
Adato et al. (US 2019/0236531 A1) teaches systems and methods for identifying products and monitoring planogram compliance using analysis of image data. In one implementation, the method may include accessing at least one planogram describing a desired placement of a plurality of product types on shelves of a plurality of retail stores; receiving image data from the plurality of retail stores; analyzing the image data to determine an actual placement of the plurality of product types on the shelves of the plurality of retail stores; determining at least one characteristic of planogram compliance based on detected differences between the at least one planogram and the actual placement of the plurality of product types on the shelves of the plurality of retail stores; and receiving checkout data from the plurality of retail stores reflecting sales of at least one product type from the plurality of product types.
Graham et al. (US 2017/0187953 A1) teaches a system and method that allows the capture of a series of images to create a single linear panoramic image is disclosed. The method includes capturing an image, dynamically comparing a previously captured image with a preview image on a display of a capture device until a overlap threshold is satisfied, generating a user interface to provide feedback on the display of the capture device to guide a movement of the capture device, and capturing the preview image with enough overlap with the previously captured image with little to no tilt for creating a linear panorama.
While the prior art teach elements of the claimed invention, they do not appear to teach the neural network performing or generating the following limitations when viewing the claimed invention as a whole: “wherein the analysis includes using the neural network unit to perform non-barcode-based object recognition that is refined based on multiple images of a given region based on plural images captured from different angles and stitching together the plural images, the objects including products and product display spaces in the retailer venue, wherein the object recognition is used to create or update at least one inventory map or planogram, wherein the created or updated at least one inventory map or planogram is compared with at least one predefined inventory map or planogram to obtain respective states of product display spaces, and wherein the output comprises electronic image information about the objects and object display spaces, based on the comparison for presentation on a display of the electronic device; (c) providing to the electronic device the output generated by said neural network unit to be presented to the user on the display of the electronic device to enable adjustment of product placement and product display inventory based on the image information.” Additionally, while each of the individual features may have been known per se, there is no teaching or suggestions absent Applicant’s own disclosure to combine these features in the specific manner claimed other than with impermissible hindsight.
Response to Arguments
Applicant's arguments filed 05/10/2026 have been fully considered but they are not persuasive. In the Remarks, Applicant argues:
Argument: “As amended, the claims (elements of Claim 1 will now be referred to if needed; Claims 27 and 28 contain parallel elements) do not relate to mental processes or fundamental economic principles or practices performed on a generic computer, as alleged in the Office Action. Office Action at 3-4. For example, outputting "electronic image information about the objects and object display spaces" cannot be performed by the human mind," nor can "providing to the electronic device [such an] output." Additionally, the operations involving analysis and generating of output are recited as being performed using a "neural network unit," which is not a "generic computer." Furthermore, the method of Claim 1 is not abstract in the sense that it is applied to a specific environment (a "retailer venue"), obtaining inputs relating to the specific environment and outputting information relating to the specific environment, the output providing information about the specific environment and enabling automated manipulation of the specific environment. To wit, this is made even more explicit in dependent Claim 29, in which the output includes a notification or recommended action, and in Claim 30, which makes a further determination regarding whether or not this has been acted upon. Finally, the neural network unit performs operations that cannot be practically performed by a human mind, such as stitching together plural images of a given region taken from different angles.”
In response, the Examiner respectfully disagrees. In Step 2A Prong One, the limitations that describe or set forth the abstract idea describe or set forth a commercial interaction (e.g., advertising, marketing or sales activities or behaviors, business relations). Commercial interactions fall within the certain method of organizing human activity enumerated grouping of abstract ideas. The limitations outlined above also describe or set forth a fundamental economic principle or practice because commercial interactions are related to commerce and economy. The limitations outlined above also describe or set forth the managing of personal behavior or relationships or interactions between people. Therefore, the claims recites a certain method of organizing human activity (Step 2A Prong One, Yes).
The limitations outlined above that exclude the additional elements, can be practically performed in the human mind. These limitations are considered a mental process because the limitations include an observation, evaluation, judgment, and/or opinion. These limitations are also similar to “collecting information, analyzing it, and displaying certain results of the collection and analysis” and/or “collecting and comparing known information” which were determined to be mental processes in MPEP 2106.04(a)(2)(III)(A). The Examiner notes that “[c]laims can recite a mental process even if they are claimed as being performed on a computer” (see MPEP 2106.04(a)(2)(III)(C)). The mere nominal recitation of the additional elements identified above do not take the claims out of the mental process grouping. Therefore, the claim recite a mental process (Step 2A Prong One, Yes).
In Steps 2A Prong Two and in Step 2B, the additional elements are recited a high level of generality, and are being used as tools, in their ordinary capacity, to perform the abstract idea. “Use of a computer or other machinery in its ordinary capacity for economic or other task (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more” (MPEP 2106.05(f)(2)). The Examiner notes that “patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101” (Recentive Analytics Inc. v. Fox Corp. (Fed. Cir. 2025)). Therefore, the claims as amended do not integrate the judicial exception into a practical application or amount to significantly more.
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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/SAM REFAI/Primary Examiner, Art Unit 3621
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