DETAILED ACTION
Status of Claims
This action is in reply to the claims filed on 30 April 2024.
Claims 1-20 are pending and have been examined.
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 .
Information Disclosure Statement
The Information Disclosure Statements filed on 30 April 2024, 14 March 2025, 08 August 2025, and 10 October 2025, have been considered. An initialed copy of the Forms 1449 are enclosed herewith.
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 rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea without significantly more).
Under step 1, it is determined whether the claims are directed to a statutory category of invention (see MPEP 2106.03(II)). In the instant case, claims 1-9 are directed to a product of manufacture (non-transitory computer-readable medium), claims 10-16 are directed to a method, and claims 17-20 are directed to a system.
While the claims fall within statutory categories, under revised Step 2A, Prong 1 of the eligibility analysis (MPEP 2106.04), the claimed invention recites an abstract idea of providing a response related to beauty topics. Specifically, representative claim 10 recites the abstract idea of:
transmitting user input and contextual information for the user input to a model,
requesting to provide a confirmation that the user input relates to one or more beauty topics;
receiving the confirmation that the user input relates to the one or more beauty topics from the model;
based on the confirmation, requesting to provide a response to the user input to be presented to a user, wherein the response relates to the one or more beauty topics and is based at least in part on the user input and the contextual information; and
receiving the response from the model.
Under revised Step 2A, Prong 1 of the eligibility analysis, it is necessary to evaluate whether the claim recites a judicial exception by referring to subject matter groupings articulated in 2106.04(a) of the MPEP. Even in consideration of the analysis, the claims recite an abstract idea. Representative claim 10 recites the abstract idea of providing a response related to beauty topics, as noted above. This concept is considered to be a method of organizing human activity. Certain methods of organizing human activity include “fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions).” MPEP 2106.04(a)(2)(II). In this case, the abstract idea recited in representative claim 10 is a certain method of organizing human activity because it relates to sale activities since the claims specifically recite transmitting user input and contextual information for the user, requesting to provide a confirmation that the user input relates to one or more beauty topics, receiving the confirmation that the user input relates to the one or more beauty topics, and based on the confirmation, requesting to provide a response to the user input to be presented to au ser where the response is related to the one or more beauty topics based on the user input and contextual information, and receiving the response from the model, thereby making this a sales activity or behavior.
Thus, representative claim 10 recites an abstract idea.
Under Step 2A, Prong 2 of the eligibility analysis, if it is determined that the claims recite a judicial exception, it is then necessary to evaluate whether the claims recite additional elements that integrate the judicial exception into a practical application of that exception. MPEP 2106.04(d). The courts have identified limitations that did not integrate a judicial exception into a practical application include limitations merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f). MPEP 2106.04(d). In this case, representative claim 10 includes additional elements: a computer, a large language model (LLM), and the LLM.
Although reciting such additional elements, the additional elements do not integrate the abstract idea into a practical application because they merely amount to no more than an instruction to apply the abstract idea using a generic computer or merely use a computer as a tool to perform the abstract idea. These additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration. Similar to the limitations of Alice, representative claim 10 merely recites a commonplace business method (i.e., providing a response related to beauty topics) being applied on a general-purpose computer using general purpose computer technology. MPEP 2106.05(f). While the claims recite a large language model, the recitations are results based in nature and do not include details as to how the model actually functioning beyond known functions. Thus, the claimed additional elements are merely generic elements and the implementation of the elements merely amounts to no more than an instruction to apply the abstract idea using a generic computer. Since the additional elements merely include instructions to implement the abstract idea on a generic computer or merely use a generic computer as a tool to perform an abstract idea, the abstract idea has not been integrated into a practical application.
Under Step 2B of the eligibility analysis, if it is determined that the claims recite a judicial exception that is not integrated into a practical application of that exception, it is then necessary to evaluate the additional elements individually and in combination to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself). MPEP 2106.05. In this case, as noted above, the additional elements of a computer, a large language model (LLM), and the LLM, recited in independent claim 10 are recited and described in a generic manner merely amount to no more than an instruction to apply the abstract idea using a generic computer or merely use a generic computer as a tool to perform an abstract idea.
Even when considered as an ordered combination, the additional elements of representative claim 1 do not add anything that is not already present when they considered individually. In Alice, the court considered the additional elements “as an ordered combination,” and determined that “the computer components…‘ad[d] nothing…that is not already present when the steps are considered separately’… [and] [v]iewed as a whole…[the] claims simply recite intermediated settlement as performed by a generic computer.” Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 217, (2014) (citing Mayo, 566 U.S. at 79, 101 USPQ2d at 1972). Similarly, when viewed as a whole, representative claim 10 simply conveys the abstract idea itself facilitated by generic computing components. Therefore, under Step 2B of the Alice/Mayo test, there are no meaningful limitations in representative claim 10 that transforms the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself.
As such, representative claim 10 is ineligible.
Independent claims 1 and 17 are similar in nature to representative claim 10, and Step 2A, Prong 1 analysis is the same as above for representative claim 10. It is noted that in independent claim 1 includes the additional elements of a non-transitory computer-readable medium having stored thereon instructions configured to, when executed by one or more computing devices of a computer system, cause the computer system to perform operations, and independent claim 17 includes the additional element of a computer system comprising a processor and a non-transitory computer-readable medium having stored thereon instructions configured to, when executed by one or more computing devices of a computer system, cause the computer system to perform operations and a client computing device. The Applicant’s specification does not provide any discussion or description of the claimed additional elements in claims 1 and 17, as being anything other than generic elements. Thus, the claimed additional elements of claims 1 and 17 are merely generic elements and the implementation of the elements merely amounts to no more than an instruction to apply the abstract idea using a generic computer. As such, the additional elements of claims 1 and 17 do not integrate the judicial exception into a practical application of the abstract idea. Additionally, the additional elements of claims 1 and 17, considered individually and in combination, do not provide an inventive concept because they merely amount to no more than an instruction to apply the abstract idea using a generic computer.
As such, claims 1 and 17 are ineligible.
Dependent claims 2-9, 11-16, and 18-20, depending from claims 1, 10 and 17 respectively, do not aid in the eligibility of the independent claims nor the representative independent claim 10. The claims of 2-9, 11-16, and 18-20 merely act to provide further limitations of the abstract idea and are ineligible subject matter.
It is noted that dependent claims include the additional elements of vector database (claims 7, 14, & 19), digital model (claims 8, 9, 15, & 20), the client computing device comprises a camera, the camera, and digital images (claim 20). Applicant’s specification does not provide any discussion or description of the claimed additional elements as being anything other than a generic element. The claimed additional elements, individually and in combination do not integrate into a practical application and do not provide an inventive concept because they are merely being used to apply the abstract idea using a generic computer (see MPEP 2106.05(f)). Accordingly, claims 7-9, 14-15, and 20 are directed towards an abstract idea. Additionally, the additional elements of claims 7-9, 14-15, and 20 considered individually and in combination, do not provide an inventive concept because they merely amount to no more than an instruction to apply the abstract idea using a generic computer. It is further noted that the remaining dependent claims 2-6, 11-13, 16, and 18-19 do not recite any further additional elements to consider in the analysis, and therefore would not provide additional elements that would integrate the abstract idea into a practical application and would not provide an inventive concept.
As such, the dependent claims 2-9, 11-16, and 18-20 are ineligible.
Claim Rejections - 35 USC § 103
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or
nonobviousness.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Yaqoob, A., et al. (PGP No. US 2025/0245731 A1), in view of Dissanayake, M. (PGP No. US 2025/0166040 A1).
Claim 1-
Yaqoob discloses a non-transitory computer-readable medium having stored thereon instructions configured to, when executed by one or more computing devices of a computer system, cause the computer system to perform operations (Yaqoob, see: paragraph [0054] disclosing “a non-transitory, computer-readable storage medium”) comprising:
transmitting user input and contextual information for the user input to a large language model (LLM) (Yaqoob, see: paragraph [0044] disclosing “the chatbot may treat the question asked by the customer as a user query and call a…large language model, to determine a query entity based on the user query and contextual information of the conversation”);
requesting the LLM to provide a confirmation that the user input relates to one or more topics (Yaqoob, see: paragraph [0044] disclosing “model is called by the item recommendation computing device 102 to determine the query entity” and “include suggested products or product types [i.e., topics]”; and paragraph [0073] disclosing “natural language model or a large language model, which is used to understand customer intent based on a conversation with a customer”)
receiving the confirmation that the user input relates to the one or more topics from the LLM (Yaqoob, see: paragraph [0044] disclosing “large language model, to determine a query entity” and “include suggested products or product types [i.e., topics]”; and see: paragraph [0073] disclosing “large language model…used to determine [i.e., confirmation] at least one query entity based on a query and contextual information”);
based on the confirmation, requesting the LLM to provide a response to the user input to be presented to a user, wherein the response relates to the one or more topics and is based at least in part on the user input and the contextual information (Yaqoob, see: paragraph [0044] disclosing “include suggested products or product types [i.e., topics]”; and paragraph [0080] disclosing “receives a search request 310 from the server 104. The search request 310 may be associated with a query and contextual information obtained from a conversation” and “the item recommendation computing device 102 transmits the item recommendation 312”); and
receiving the response from the LLM (Yaqoob, see: paragraph [0044] disclosing “a large language model, to determine a query entity based on the user query and contextual information” and “model is called by the item recommendation computing device 102 to determine the query entity, which include suggested products or product types” and “generate a ranked list of recommended items” and “may transmit some or all of the recommended items…to be displayed to the customer”; See paragraph [0088], also describing that the system provides the customer a response including recommendations of items via the user interface.).
Although Yaqoob discloses the suggested products or product types that are of interest that is determined by the input and contextual information, Yaqoob does not disclose that the topics are related to beauty topics. Yaqoob does not disclose:
input relates to one or more beauty topics;
response relates to one or more beauty topics;
Dissanayake, however, does teach:
input relates to one or more beauty topics (Dissanayake, see: paragraph [0041] teaching “pigmented spots (e.g., hemoglobin and/or melanin) may be identified by the user” and “Through a conversation, the user can describe these features”; and see: paragraph [0117] teaching “interface 602 may also include or render a user-specific skin issue 610” and “comprises a message 610m”; Also see FIG. 6 depicting the user interface allowing the user to indicate the topics of concern, such as pigmented spots of the skin.);
response relates to one or more beauty topics (Dissanayake, see: paragraph [0118] teaching “message 612m indicates to a user that the user-specific issue and/or condition is mild…issue results from pigmented spots at the indicated region of the user’s skin” and “recommends to the user to use a night face cream to help reduce the pigmented spots”; Also see: FIG. 6).
This step of Dissanayake is applicable to the product of manufacture of Yaqoob, as they both share characteristics and capabilities, namely, they are directed to recommending items to customers based on conversations. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify product of manufacture of Yaqoob, to include the features of input relates to one or more beauty topics and response relates to one or more beauty topics, as taught by Dissanayake. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify the reference of Yaqoob to improve the responses regarding beauty products to customers in order to provide improved product recommendations (Dissanayake, see: paragraph [0007]).
Claim 2-
Yaqoob in view of Dissanayake teach the computer-readable medium of Claim 1, as described above.
Yaqoob discloses:
wherein requesting the LLM to provide the confirmation that the user input relates to the one or more topics comprises requesting the LLM to provide one or more classifications of the user input (Yaqoob, see: paragraph [0069] disclosing “item categories 348 identifying a product type (or category) of each item”),
wherein receiving the confirmation that the user input relates to the one or more topics comprises receiving the one or more classifications of the user input from the LLM (Yaqoob, see: paragraph [0073] disclosing “a large language model, which is used to understand customer intent based on a conversation with a customer” and “model 392 is used to determine at least one query entity based on a query and contextual information submitted”), and
wherein the one or more classifications indicate that the user input relates to one or more topics (Yaqoob, see: paragraph [0069] disclosing “item categories 348 identifying a product type (or category) [i.e., relates to one or more topics] of each item”; and paragraph [0073] disclosing “product type or product category based on the general-purpose language understanding of the query and the contextual information”).
Yaqoob does not disclose:
one or more beauty topics;
Dissanayake, however, does teach:
one or more beauty topics (Dissanayake, see: paragraph [0038] teaching “user to converse with a natural language model to provide natural langue data defining a skin issue(s), condition(s), or concern(s)”).
This step of Dissanayake is applicable to the product of manufacture of Yaqoob, as they both share characteristics and capabilities, namely, they are directed to recommending items to customers based on conversations. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify product of manufacture of Yaqoob, to include the features of one or more beauty topics, as taught by Dissanayake. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify the reference of Yaqoob to improve the responses regarding beauty products to customers in order to provide improved product recommendations (Dissanayake, see: paragraph [0007]).
Claim 3-
Yaqoob in view of Dissanayake to teach the computer-readable medium of Claim 2, as described above.
Yaqoob further discloses wherein requesting the LLM to provide one or more classifications of the user input comprises:
requesting the LLM to provide a first classification of the user input (Yaqoob, see: paragraph [0031] disclosing “a user may first ask for wedding clothes with a blue color theme” and paragraph [0032] disclosing “merge the query entities together based on their similarity to each other and/or an LLM. The system can also extract facets and keywords associated with an item”);
receiving the first classification of the user input from the LLM, wherein the first classification indicates that the user input relates to the one or more topics (Yaqoob, see: paragraph [0031] disclosing “a user may first ask for wedding clothes with a blue color theme”); and
responsive to the first classification indicating that the user input relates to the one or more topics, requesting the LLM to provide a second classification of the user input that further defines the one or more topics, wherein requesting the LLM to provide the response to the user input is based on both the first classification and the second classification (Yaqoob, see: paragraph [0031] disclosing “Then the same user can ask for ties and bowties. The chatbot will be able to maintain the context of blue color theme and suggest ties and bowties which match that context”).
Yaqoob does not disclose one or more beauty topics,
Dissanayake, however, does teach:
one or more beauty topics (Dissanayake, see: paragraph [0038] teaching “user to converse with a natural language model to provide natural langue data defining a skin issue(s), condition(s), or concern(s)”).
This step of Dissanayake is applicable to the product of manufacture of Yaqoob, as they both share characteristics and capabilities, namely, they are directed to recommending items to customers based on conversations. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify product of manufacture of Yaqoob, to include the features of one or more beauty topics, as taught by Dissanayake. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify the reference of Yaqoob to improve the responses regarding beauty products to customers in order to provide improved product recommendations (Dissanayake, see: paragraph [0007]).
Claim 4-
Yaqoob in view of Dissanayake teach the computer-readable medium of Claim 1, as described above.
Yaqoob discloses wherein the user input includes text input or voice input (Yaqoob, see: paragraph [0057] disclosing “data input…can include one or more of a keyboard…a touchscreen… speaker, a microphone”; and paragraph [0074] disclosing “transform the text of a query into a query embedding vector”).
Claim 5-
Yaqoob in view of Dissanayake teach the computer-readable medium of Claim 1, as described above.
Yaqoob discloses the operations further comprising requesting the LLM to provide a summary of the user input (Yaqoob, see: paragraph [0074] disclosing “model 393 may be used to encode a query or a product item into an embedding” and “used to transform each query entity name (which may be a product name, product type name, product category name, product family name, or product department name) into an embedding vector in the vector space”; and paragraph [0075] disclosing “In some embodiments, the grouping model 394 is used to compare embedding vectors of two query entities” and “model 394 includes an LLM configured to determine whether two query entities should be organized into a same group for display”).
Claim 6-
Yaqoob in view of Dissanayake teach the computer-readable medium of Claim 5, as described above.
Yaqoob discloses:
the operations further comprising: receiving the summary of the user input from the LLM; generating a vector representation of the user input (Yaqoob, see: paragraph [0102] disclosing “sentence encoder 430 performs sentence embedding to transform textual data 910 into a numerical vector 912” and “the textual data 910 can be replaced by any product name or any query entity name, e.g. a name of the query entity X 810 or the query entity Y 820, to generate a corresponding embedding vector”; Also see: FIG. 9).
Claim 7-
Yaqoob in view of Dissanayake teach the computer-readable medium of Claim 6, as described above.
Yaqoob discloses the operations further comprising:
comparing the vector representation of the user input with vector representations of other vector representations in a vector database (Yaqoob, see: paragraph [0077] disclosing “can compare these vector embeddings with an embedding of the enhanced query to determine, among the most commonly searched queries” and “a nearest neighbor index can be utilized in the vector embedding database for fast search and retrieval”); and
identifying a near-neighbor match for the vector representation of the user input among the other vector representations in the vector database (Yaqoob, see: paragraph [0077] disclosing “a nearest neighbor index can be utilized in the vector embedding database for fast search and retrieval” and “then map the most similar query back to a set of product items”).
Claim 8-
Yaqoob in view of Dissanayake teach the computer-readable medium of Claim 1, as described above.
Yaqoob discloses the operations further comprising: requesting the LLM to generate a product recommendation (Yaqoob, see: paragraph [0044] disclosing “large language model…is called by the item recommendation computing device 102 to determine the query entity, which include suggested products”).
Yaqoob does not disclose:
obtaining a digital model of a face of the user ; and
a care routine recommendation based at least in part on the digital model of the face.
Dissanayake, however, does teach:
obtaining a digital model of a face of the user (Dissanayake, see: paragraph [0095] disclosing “Digital twin image 202a-dt is generated based on the 202a’s information”); and
a care routine recommendation based at least in part on the digital model of the face (Dissanayake, see: paragraph [0118] teaching “recommends to the user to use a night face cream to help reduce the pigmented spots” and “output by AI models based on the natural language data and/or digital twin image” and “recommendation can be correlated to the identified feature within the pixel data”).
This step of Dissanayake is applicable to the product of manufacture of Yaqoob, as they both share characteristics and capabilities, namely, they are directed to recommending items to customers based on conversations. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify product of manufacture of Yaqoob, to include the features of obtaining a digital model of a face of the user and a care routine recommendation based at least in part on the digital model of the face, as taught by Dissanayake. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify the reference of Yaqoob to improve the responses regarding beauty products to customers in order to provide improved product recommendations (Dissanayake, see: paragraph [0007]).
Claim 9-
Yaqoob in view of Dissanayake teach the computer-readable medium of Claim 8, as described above.
Yaqoob does not disclose wherein the digital model of the face includes a plurality of skin features including blemish information, hyper-pigmentation information, clinical signs, skin concern information, skin texture information, skin tone information, or a combination thereof.
Dissanayake however, does teach:
wherein the digital model of the face includes a plurality of skin features including blemish information, hyper-pigmentation information, clinical signs, skin concern information, skin texture information, skin tone information, or a combination thereof (Dissanayake, see: paragraph [0104] teaching “spot IDs may comprise a range (e.g., IDs 1-20) for identifying various levels of pigmentations or intensities of the skin (e.g., caused by hemoglobin, melanin, acne, etc.) as identifiable within the pixel data”; Also see: FIG. 4B).
This step of Dissanayake is applicable to the product of manufacture of Yaqoob, as they both share characteristics and capabilities, namely, they are directed to recommending items to customers based on conversations. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify product of manufacture of Yaqoob, to include the features of wherein the digital model of the face includes a plurality of skin features including blemish information, hyper-pigmentation information, clinical signs, skin concern information, skin texture information, skin tone information, or a combination thereof, as taught by Dissanayake. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify the reference of Yaqoob to improve the responses regarding beauty products to customers in order to provide improved product recommendations (Dissanayake, see: paragraph [0007]).
Regarding claim 10, claim 10 is directed to a method. Claim 10 recites limitations that are parallel in nature to those addressed above for claim 1 which is directed towards a product of manufacture. Claim 10 is therefore rejected for the same reasons as set forth above for claim 1.
Regarding claim 11, claim 11 is directed to a method. Claim 11 recites limitations that are parallel in nature to those addressed above for claim 2 which is directed towards a product of manufacture. Claim 11 is therefore rejected for the same reasons as set forth above for claim 2.
Regarding claim 12, claim 12 is directed to a method. Claim 12 recites limitations that are parallel in nature to those addressed above for claim 3 which is directed towards a product of manufacture. Claim 12 is therefore rejected for the same reasons as set forth above for claim 3.
Regarding claim 13, claim 13 is directed to a method. Claim 13 recites limitations that are parallel in nature to those addressed above for claim 6 which is directed towards a product of manufacture. Claim 13 is therefore rejected for the same reasons as set forth above for claim 6.
Regarding claim 14, claim 14 is directed to a method. Claim 14 recites limitations that are parallel in nature to those addressed above for claim 7 which is directed towards a product of manufacture. Claim 14 is therefore rejected for the same reasons as set forth above for claim 7.
Regarding claim 15, claim 15 is directed to a method. Claim 15 recites limitations that are parallel in nature to those addressed above for claim 8 which is directed towards a product of manufacture. Claim 15 is therefore rejected for the same reasons as set forth above for claim 8.
Regarding claim 16, claim 16 is directed to a method. Claim 16 recites limitations that are parallel in nature to those addressed above for claim 9 which is directed towards a product of manufacture. Claim 16 is therefore rejected for the same reasons as set forth above for claim 9.
Regarding claim 17, claim 17 is directed to a system. Claim 17 recites limitations that are similar in nature to those addressed above for claim 1 which is directed towards a product of manufacture. It is noted that claim 17 also includes a computer system comprising a processor and a non-transitory computer read-able medium, which is disclosed by Yaqoob (Yaqoob, see: paragraph [0054] disclosing “one or more processors 201”). Claim 17 is therefore rejected for the same reasons as set forth above for claim 1.
Regarding claim 18, claim 18 is directed to a system. Claim 18 recites limitations that are similar in nature to those addressed above for claim 3 which is directed towards a product of manufacture. Claim 18 is therefore rejected for the same reasons as set forth above for claim 3.
Regarding claim 19, claim 19 is directed to a system. Claim 19 recites limitations that are similar in nature to those addressed above for claims 7, 13 and 14, which are directed towards a product of manufacture. Claim 19 is therefore rejected for the same reasons as set forth above for claim 7, 13, and 14.
Claim 20-
Yaqoob in view of Dissanayake teach the computer system of Claim 17, as described above.
Yaqoob discloses requesting the LLM to generate a product recommendation (Yaqoob, see: paragraph [0044] disclosing “large language model…is called by the item recommendation computing device 102 to determine the query entity, which include suggested products”).
Yaqoob does not disclose:
wherein the client computing device comprises a camera, the operations further comprising: causing the client computing device to request activation of the camera to capture one or more digital images;
receiving the one or more captured digital images;
generating a digital model of the face of the user based at least in part on the one or more captured digital images; and
a care routine recommendation based at least in part on the digital model of the face.
Dissanayake, however, does teach:
wherein the client computing device comprises a camera, the operations further comprising: causing the client computing device to request activation of the camera to capture one or more digital images (Dissanayake, see: paragraph [0092] teaching “Each of the digital twin images may comprise photorealistic images comprising pixel data, for example, as would have been captured by a digital camera”);
receiving the one or more captured digital images; (Dissanayake, see: paragraph [0095] disclosing “Digital twin image 202a-dt is generated based on the 202a’s information”);
generating a digital model of the face of the user based at least in part on the one or more captured digital images (Dissanayake, see: paragraph [0095] disclosing “Digital twin image 202a-dt is generated based on the 202a’s information”); and
a care routine recommendation based at least in part on the digital model of the face (Dissanayake, see: paragraph [0118] teaching “recommends to the user to use a night face cream to help reduce the pigmented spots” and “output by AI models based on the natural language data and/or digital twin image” and “recommendation can be correlated to the identified feature within the pixel data”).
This step of Dissanayake is applicable to the system of Yaqoob, as they both share characteristics and capabilities, namely, they are directed to recommending items to customers based on conversations. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Yaqoob, to include the features of wherein the client computing device comprises a camera, the operations further comprising: causing the client computing device to request activation of the camera to capture one or more digital images, receiving the one or more captured digital images, generating a digital model of the face of the user based at least in part on the one or more captured digital images, and a care routine recommendation based at least in part on the digital model of the face, as taught by Dissanayake. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify the reference of Yaqoob to improve the responses regarding beauty products to customers in order to provide improved product recommendations (Dissanayake, see: paragraph [0007]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Newman, R., et al. (PGP No. US 2024/0427999 A1), describes a computing device that receives a first conventional input of one or more sequential conversational inputs via one or more user input devices.
NPL document I Let ChatGPT Decide My Skin-Care Routine for a Month — Here’s How It Went, published allure.com (2024), describes an interface that utilizes Generative AI to intake large amounts of data to provide beauty and skin care routines and recommendations to online users.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ASHLEY PRESTON whose telephone number is (571)272-4399. The examiner can normally be reached M-F 9-5.
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/ASHLEY D PRESTON/Primary Examiner, Art Unit 3688