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
This action is in reply to the communications filed on June 9, 2026. The Applicants’ Amendment and Request for Reconsideration has been received and entered.
Claims 1-4, 8-14, 17-18, and 21-24 are currently pending and have been examined. Claims 1, 14, and 17 have been amended. Claims 5-7, 15-16, and 19-20 have been canceled. Claims 21-24 are newly added.
The previous objection to claim 15 has been withdrawn.
Examiner’s Note: The Examiner notes that claims 23-24 are eligible under 35 USC 101. The Examiner notes that claim 23 recites an abstract idea that constitutes a mental process. However, the Examiner further notes that the abstract idea is integrated into a practical application. For example, claim 23 recites displaying, via the user interface of the web browser, text describing the first item, an image of the first item, a first selection field for receiving a selection of the first item, and the text answer to the query, wherein the image displays an attribute of the first item; receiving, via the user interface of the web browser, a selection of the first item via the first selection field and a follow-up query input via the text input field, wherein the follow-up query refers to the displayed attribute of the first item and describes a modification to the displayed attribute of the first item; executing a second search responsive to receiving the follow-up query, wherein executing the second search comprises: generating a second search embedding corresponding to a combination of the follow-up query, the text describing the first item, the image of the first item, and a conversation history; and selecting a second item based on the second search embedding by comparing the second search embedding with an embedding in the collection of pre-computed embeddings corresponding to the second item; by the dialog controller, generating a follow-up text answer to the follow-up query, wherein the follow-up text answer refers to the second item; and displaying, via the user interface of the web browser, second text describing the second item, a second image of the second item, a second selection field for receiving a selection of the second item, and the follow-up text answer to the follow-up query, wherein the second image displays the modification to the attribute of the first item. The combination of at least these elements uses the judicial exception in a 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.
Response to Arguments
Applicants’ amendments necessitated any new grounds of rejection.
The previous objection to claim 15 has been withdrawn in view of the cancellation of claim 15.
Applicants’ arguments regarding the rejection of claims 1 and 14 under 35 USC 101 have been fully considered but they are not persuasive. Regarding claim 1, Applicants assert at page 13 of Applicants’ Reply dated June 9, 2026 (hereinafter “Applicants’ Reply”) that “amended claim 1 cannot be performed in the mind” and point to the limitations regarding generating training instances, fine-tuning the model, and generating embeddings. The Examiner respectfully disagrees.
Per MPEP 2106.04(a)(2)(III)(A), examples of claims that do not recite mental processes because they cannot be practically performed in the human mind include: a claim to a method for calculating an absolute position of a GPS receiver and an absolute time of reception of satellite signals, where the claimed GPS receiver calculated pseudoranges that estimated the distance from the GPS receiver to a plurality of satellites; a claim to detecting suspicious activity by using network monitors and analyzing network packets; a claim to a specific data encryption method for computer communication involving a several-step manipulation of data; and a claim to a method for rendering a halftone image of a digital image by comparing, pixel by pixel, the digital image against a blue noise mask, where the method required the manipulation of computer data structures (e.g., the pixels of a digital image and a two-dimensional array known as a mask) and the output of a modified computer data structure (a halftoned digital image).
In contrast, claims do recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. Examples of claims that recite mental processes include: a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind; claims to "comparing BRCA sequences and determining the existence of alterations," where the claims cover any way of comparing BRCA sequences such that the comparison steps can practically be performed in the human mind; a claim to collecting and comparing known information, which are steps that can be practically performed in the human mind; and a claim to identifying head shape and applying hair designs, which is a process that can be practically performed in the human mind).
Further, per MPEP 2106.04(a)(2)(III)(C), “Claims can recite a mental process even if they are claimed as being performed on a computer.” Thus, merely reciting the use of a computer is not sufficient to recite a technological improvement. MPEP 2106.04(a)(2)(III)(C) further indicates “In evaluating whether a claim that requires a computer recites a mental process, examiners should carefully consider the broadest reasonable interpretation of the claim in light of the specification. For instance, examiners should review the specification to determine if the claimed invention is described as a concept that is performed in the human mind and applicant is merely claiming that concept performed 1) on a generic computer, or 2) in a computer environment, or 3) is merely using a computer as a tool to perform the concept. In these situations, the claim is considered to recite a mental process.”
With this guidance in mind, the Examiner respectfully asserts that the instant claims recite a mental process that can be done with pen and paper or in the human mind or by using a computer as a tool to perform the method. Gathering user data and applying a model to make a prediction as to user behavior or the outcome of user behavior include observations, evaluations, judgments, and opinions, i.e., a mental process.
Regarding the generating the plurality of questions and the plurality of ground truth answers, no detail is provided regarding the “template”, how it is structured, and how it produces the questions and answers. For example, is the template a separate machine learning model that generates questions based on prior user data? Absent any details about this template, the template may be considered merely using a computer as a tool to perform the mental process.
Regarding the fine-tuning, is this an iterative process? If so, how is it determined when fine-tuning/updating of the model is needed? Is it an automatic process based on a threshold accuracy between the ground-truth answers/predictions and the actual answers/actions? For example, does the multi-modal machine learning model determine for itself when it is time to be fine-tuned/updated/retrained based on accuracy of predictions? Is the result of the recommendation, i.e., the outcome of the recommendation, part of the iterative process? Otherwise, if the iterative process is performed routinely or at the direction of a user, the fine-tuning may be considered a mental process or merely using a computer as a tool to perform the mental process.
Further, as discussed further below, it is unclear what is meant by “updating a weight of the multi-modal machine learning model.” If this is merely updating any weight of the multi-modal machine learning model, then this step may be considered a mental process or merely using a computer as a tool to perform the mental process. For example, if the questions and answers are about a particular feature of the item, a human user would know to weight any parameters corresponding to that particular feature in the model.
Applicants further argue at page 16 of Applicants’ Reply that “Even if amended claim 1 recites a mental process, this alleged mental process is integrated into a practical application” and that the previously-discussed limitations “improve a machine learning model itself and improve a computer application that implements the machine learning model.” The Examiner respectfully disagrees.
Per MPEP 2106.04(d), in order to determine if a claim integrates the judicial exception into a practical application, the considerations set forth in MPEP 2106.05 (a)-(c) and (e)-(h) are evaluated. MPEP 2106.04(d) clearly states that “a specific way of achieving a result is not a stand-alone consideration... However, the specificity of the claim limitations is relevant to the evaluation of several considerations including the use of a particular machine, particular transformation and whether the limitations are mere instructions to apply an exception.” The Examiner notes that the considerations include improvements to computer functionality, improvements to any other technology or technical field, and a particular machine or transformation.
Further, per MPEP 2106.05(a), in order to constitute a technical improvement, the specification "must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology." Further, per MPEP 2106.05(a), "if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement."
Per MPEP 2106.05(a), improvements to computer functionality include a modification of conventional Internet hyperlink protocol to dynamically produce a dual-source hybrid webpage; inventive distribution of functionality within a network to filter Internet content; a method of rendering a halftone digital image; a distributed network architecture operating in an unconventional fashion to reduce network congestion while generating networking accounting data records; a memory system having programmable operational characteristics that are configurable based on the type of processor, which can be used with different types of processors without a tradeoff in processor performance; technical details as to how to transmit images over a cellular network or append classification information to digital image data; a particular structure of a server that stores organized digital images; a particular way of programming or designing software to create menus; a method that generates a security profile that identifies both hostile and potentially hostile operations, and can protect the user against both previously unknown viruses and "obfuscated code," which is an improvement over traditional virus scanning; an improved user interface for electronic devices that displays an application summary of unlaunched applications, where the particular data in the summary is selectable by a user to launch the respective application; a specific interface and implementation for navigating complex three-dimensional spreadsheets using techniques unique to computers; and a specific method of restricting software operation within a license.
Per MPEP 2106.05(a), some examples that the courts have said “may not be sufficient to show an improvement in computer-functionality” include generating restaurant menus with functionally claimed features; accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer; mere automation of manual processes, such as using a generic computer to process an application for financing a purchase; recording, transmitting, and archiving digital images by use of conventional or generic technology in a nascent but well-known environment, without any assertion that the invention reflects an inventive solution to any problem presented by combining a camera and a cellular telephone; affixing a barcode to a mail object in order to more reliably identify the sender and speed up mail processing, without any limitations specifying the technical details of the barcode or how it is generated or processed; instructions to display two sets of information on a computer display in a non-interfering manner, without any limitations specifying how to achieve the desired result; providing historical usage information to users while they are inputting data, in order to improve the quality and organization of information added to a database, because "an improvement to the information stored by a database is not equivalent to an improvement in the database’s functionality”; and arranging transactional information on a graphical user interface in a manner that assists traders in processing information more quickly.
With this guidance in mind, the Examiner respectfully asserts that the claims are not directed to a practical application. Applicants reference paragraphs [0027]-[0030] at page 17 of Applicants’ Reply as evidence for technical improvements. However, the alleged improvements discussed in these paragraphs are not technical improvements because they are not improvements to “computer functionality, improvements to any other technology or technical field, and a particular machine or transformation.” Instead, these paragraphs discuss an improvement to an interactive recommender system or search tool and reference that “the accuracy, precision, and generalizability of these system and tools may be improved.” An improvement to a recommender system is not an improvement to computer functionality or an improvement to a technology or technical field. Instead, it is an alleged improvement to a recommendation system, i.e., the abstract idea itself.
Applicants further reference the Enfish decision at pages 17-18 of Applicants’ Reply and assert at page 18 that “claim 1 provides an improvement to computer technology—specifically a process for training computer models in a manner that improves the computer models themselves and for transferring that learning into a chat bot, which improves the chat bot itself.” The Examiner respectfully disagrees. The claims do not recite a process for training computer models; instead, claim 1 merely recites generating training instances and generating questions and answers using a template. However, no details about the template are actually recited. Further, there is no recitation in claim 1 of transferring anything to a chat bot. Applicants are invited to further elaborate on this.
Regarding the Enfish decision, the court in Enfish drew a distinction between a business solution and a technical solution by finding it "relevant to ask whether the claims are directed to an improvement to computer functionality versus being directed to an abstract idea” and asked "whether the focus of the claims is on the specific asserted improvement in computer capabilities (i.e., the self-referential table for a computer database) or, instead, on a process that qualifies as an ’abstract idea’ for which computers are invoked merely as a tool.” The Enfish court concluded that “the plain focus of the claims is on an improvement to computer functionality itself, not on economic or other tasks for which a computer is used in its ordinary capacity.”
With this guidance in mind, the Examiner respectfully asserts that the instant claims are directed to using existing computers as tools to perform the abstract idea, i.e., using a machine learning model to perform a mental process rather than an improvement in computer capabilities like the self-referential database in Enfish, i.e., a technological solution. As the Examiner stated above, no actual technical structure of the template for example is provided or how the template generates the questions and answers.
Applicants further argue at page 18 of Applicants’ Reply that in Ex parte Desjardins, “found that a claim that improves operation of a machine learning model is patent eligible.” The Examiner respectfully disagrees with Applicants’ interpretation of Desjardins regarding the instant claims.
Per the Appeal Review Panel Decision in Ex parte Desjardins, per MPEP 2106.04(d)(1), “the specification identified the improvement to machine learning technology by explaining how the machine learning model is trained to learn new tasks while protecting knowledge about previous tasks to overcome the problem of “catastrophic forgetting,” and that the claims reflected the improvement identified in the specification. Indeed, enumerated improvements identified in the Desjardins specification included disclosures of the effective learning of new tasks in succession in connection with specifically protecting knowledge concerning previously accomplished tasks; allowing the system to reduce use of storage capacity; and the enablement of reduced complexity in the system. Such improvements were tantamount to how the machine learning model itself would function in operation and therefore not subsumed in the identified mathematical calculation.”
With this in mind, the Examiner respectfully notes that, in Ex parte Desjardins, the claim reflected the technological improvement because the claim identifies how the machine learning model is actually trained, i.e., assigning values and using training data to adjust those values to optimize a particular function. However, Applicants’ instant claims do not recite how the machine learning model is actually trained, i.e., assigning values and using training data to adjust those values to optimize a particular function. Thus, the instant claims are not similar to those in Desjardins. As the Examiner has noted above and below, claim 1 is unclear regarding updating the weight of the model and what the weight actually represents. No actual parameters or values of the model are actually discussed and there is no discussion of optimization of the model either. Thus, Desjardins does not apply.
Applicants further argue at page 18 of Applicants’ Reply that “amended claim 1 cannot reasonably be interpreted to preempt all applications of any mental process.” The Examiner respectfully notes that, per MPEP 2106.04, while “preemption is the concern underlying...the judicial exception, it is not a standalone test for determining eligibility... Instead questions of preemption are inherent in and resolved by the two-part framework from Alice Corp. and Mayo....It is necessary to evaluate eligibility using the Alice/Mayo test, because while a preemptive claim may be ineligible, the absence of complete preemption does not demonstrate that a claim is eligible.”
Thus, the rejection of claims 1 and 14 under 35 USC 101 is maintained.
Applicants’ remaining arguments have been fully considered but they have either been addressed above or they are moot in view of the new grounds of rejection.
Claim Rejections - 35 USC § 112
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.
Claims 1-4, 8-14, 17-18, and 21-22 are 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.
Claims 1-4, 8-14, 17-18, and 21-22: Claim 1 recites “updating a weight of the multi-modal machine learning model based on comparing the predicted answer to the ground truth answer.” This limitation is unclear. What weight is this referring to? Is this a parameter applied to the entire model itself, i.e. a measure of the accuracy of the model? Or is this the weight of a particular parameter of the model? If the latter, how is this parameter determined? How is the weight adjusted based on the comparison of the predicted to the ground truth answer? For purposes of examination, the Examiner is interpreting this portion of claim 1 as reciting “updating at least one weight of the multi-modal machine learning model based on comparing the predicted answer to the ground truth answer.”
Claim 14 is rejected for similar reasons.
Claims 2-4, 8-13, 17-18, and 21-22 inherit the deficiencies of claims 1 and 14.
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, 8-14, 17-18, and 21-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent claims 1 and 14 recite a method and a system for recommending items. With regard to claim 1, the limitations of generating training instances, accessing an image, accessing structured text, parsing the structured text, generating a plurality of questions and answers, forming a question-answer-image triplet, fine-tuning the model, appending a classification layer, generating a predicted answer, comparing the predicted answer to the ground truth answer, updating a weight, generating a collection of embeddings for a collection of items, determining a first embedding for a selected item, determining a second embedding for the user query, determining a third embedding for a conversation history, generating a target embedding, determining similarities, and recommending an item, as drafted, illustrate a series of steps that, under their broadest reasonable interpretation, cover a mental process. That is, other than reciting that a processor performs the method (in claim 14), nothing in the claim precludes the steps from practically being performed in the mind. Claim 14 recites similar limitations.
The judicial exception is not integrated into a practical application. In particular, claims 1 and 14 recite receiving data. These limitations are considered to be insignificant extra-solution activity. Further, claim 14 recites a processor and a memory at a high level of generality (i.e., as generic computer components performing generic computer functions). Accordingly, these elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Thus, claims 1 and 14 are directed to the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, claims 1 and 14 recite receiving data. Per MPEP 2106.05(d)(II), elements such as receiving or transmitting data over a network, using the Internet to gather data, and storing and retrieving information in memory are considered to be computer functions that are well-understood, routine, and conventional functions. See Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPG2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)).
Further, as discussed above with respect to integration of the abstract idea into a practical application, the claims recite a processor and a memory at a high level of generality (i.e., as generic computer components performing generic computer functions). Mere instructions to apply an exception using generic computer components cannot provide an inventive concept.
Additionally, the independent claims recite a multi-modal machine learning model. The Examiner notes that in paragraph [0032] of the published application, Applicants list various models that may constitute the multi-modal machine learning model including CLIP, MUTAN, MCAN, BUTD, ALIGN, VLBERT, VisualBERT, and variations of such models, or another model. Applicants do not describe the particulars of the models, indicating that the models are sufficiently well-known. Thus, the Examiner interprets a multi-modal machine learning model as a well-understood, routine, or conventional element.
Thus, claims 1 and 14 are not patent eligible.
Claims 2-4, 8-13, and 17-18 depend from claims 1 and 14. Claim 2 is directed to performing the steps of claim 1 again with respect to a first recommended item and is further directed to the abstract idea. Claim 3 is directed to receiving data which, as discussed above, is a function that is considered to be well-understood, routine, and conventional. Claim 4 is directed to the type of item and selecting the item and is further directed to the abstract idea. Claim 8 is directed to receiving a selection of the item, the composition of the items, determining the first embeddings, and averaging the first embeddings and is further directed to the abstract idea. Claim 9 is directed to the type of model and is further directed to the abstract idea. Claim 10 is directed to determining the similarities and is further directed to the abstract idea. Claim 11 is directed to the type of item text and is further directed to the abstract idea. Claim 12 is directed to the type of conversation history and is further directed to the abstract idea. Claim 13 is directed to determining the conversation state embeddings and determining a weighted average and is further directed to the abstract idea. Claim 17 is directed to the type of training item and is further directed to the abstract idea. Claim 18 is directed to a purchase link for the recommended item, receiving a selection of the link, and adding the recommended item to a shopping cart and is further directed to the abstract idea.
Thus, the claims are not patent eligible.
Allowable Subject Matter
Claims 23-24 are allowed.
With respect to claim 23, the prior art of record, neither alone nor combined, neither anticipates nor renders obvious a method comprising: generating a collection of pre-computed embeddings for a collection of items; receiving, via a user interface of a web browser, a query via a text input field; executing a first search responsive to receiving the query, wherein executing the first search comprises: generating a first search embedding corresponding to the query; and selecting a first item using the first search embedding by comparing the first search embedding with an embedding in the collection of pre-computed embeddings corresponding to the first item; by a dialog controller, generating a text answer to the query, wherein the text answer refers to the first item; displaying, via the user interface of the web browser, text describing the first item, an image of the first item, a first selection field for receiving a selection of the first item, and the text answer to the query, wherein the image displays an attribute of the first item; receiving, via the user interface of the web browser, a selection of the first item via the first selection field and a follow-up query input via the text input field, wherein the follow-up query refers to the displayed attribute of the first item and describes a modification to the displayed attribute of the first item; executing a second search responsive to receiving the follow-up query, wherein executing the second search comprises: generating a second search embedding corresponding to a combination of the follow-up query, the text describing the first item, the image of the first item, and a conversation history; and selecting a second item based on the second search embedding by comparing the second search embedding with an embedding in the collection of pre-computed embeddings corresponding to the second item; by the dialog controller, generating a follow-up text answer to the follow-up query, wherein the follow-up text answer refers to the second item; and displaying, via the user interface of the web browser, second text describing the second item, a second image of the second item, a second selection field for receiving a selection of the second item, and the follow-up text answer to the follow-up query, wherein the second image displays the modification to the attribute of the first item.
In the event the claims are amended, they will be subject to further examination.
Potentially Allowable Subject Matter
Claims 1-4, 8-14, and 17-18 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, and 35 USC 101 set forth in this Office action.
Claims 21-22 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
In the event the claims are amended, they will be subject to further examination.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2021/0342914 A1 to Dalal et al. is directed to systems “to identify products comprising: product vector database; a plurality of portable computing devices comprising a camera and a control circuit configured to: access an image captured by the camera; perform an optical character recognition on the image; apply a vector modeling rule to key text, generate a first query product vector and wirelessly communicate the first query product vector to the product recommendation system; the product recommendation system is configured to apply a vector evaluation rule to the first query product vector to identify a first product; and wirelessly communicate to the portable computing device the first product identifier.” (See Abstract).
US 12,222,937 B2 to Na et al. is directed to an “online concierge system [that] maintains various items and an item embedding for each item. When the online concierge system receives a query for retrieving one or more items, the online concierge system generates an embedding for the query. The online concierge system trains a machine-learned model to determine a measure of relevance of an embedding for a query to item embeddings by generating training data of examples including queries and items with which users performed a specific interaction.” See Abstract).
US 11,741,139 B2 to Zhuo et al. is directed to systems and methods “for providing a response to a user query…An augmentation machine learning model is utilized to determine one or more variations of the user query that correspond to a semantic meaning of the user query. A plurality of response candidates is determined that correspond to the user query by comparing the user query and the one or more variations of the user query to a plurality of documents. A final response candidate is determined from the plurality of response candidates based on utilizing a semantic machine learning model to perform a semantic comparison between the plurality of response candidates and at least the user query.” (See Abstract).
US 11,488,223 B1 to Suprasadachandran et al. is directed to a “user interface (UI) feature [that] assists users in comparing items and making purchase decisions.” (See Abstract).
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 extension fee 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 date of this final action.
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/Anne M Georgalas/
Primary Examiner, Art Unit 3689
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