Bundling curation by generative artificial intelligence

Abstract

The invention describes a binding curation by generative artificial intelligence. A cue is generated for input to the generative artificial intelligence to create a harness including the seed article of apparel based on the seed article of apparel. The cue is provided to the generative artificial intelligence to cause the generative artificial intelligence to initiate a search for the online marketplace to locate complementary items of apparel available on the online marketplace for clothing. In response to a search initiated by generative artificial intelligence, search results containing a list of complementary items of apparel available on the online marketplace for clothing are received. A list of complementary apparel items for clothing is arranged in a user interface for user selection.

Description

[0001] Related Applications

[0002] This application claims priority under 35 U.S.C. §119(e) to U.S. Provisional Patent Application No. 63 / 519,213, filed on August 11, 2023, entitled “Outfit Curation by Generative Artificial Intelligence,” the entire disclosure of which is incorporated herein by reference. Background Art

[0003] Online retailers may curate outfits to create visually appealing and overall coordinated looks that inspire customers and drive sales. Such curation typically involves designers manually selecting clothing, accessories, and other items from a retailer's inventory in a way that showcases their products in the best possible light while also catering to the preferences and needs of their target audience. Summary of the invention

[0004] Outfit curation by generative artificial intelligence via an online marketplace. In one or more implementations, a prompt is generated for input to the generative artificial intelligence to create an outfit including the seed item of clothing based on a seed item of clothing. The prompt is provided to the generative artificial intelligence so that the generative artificial intelligence initiates a search of the online marketplace to locate complementary items of clothing for the outfit available on the online marketplace. In response to the search initiated by the generative artificial intelligence, search results are received that include a list of complementary items of clothing for the outfit available on the online marketplace. The list of complementary items of clothing for the outfit is arranged in a user interface for selection by a user.

[0005] This summary introduces a selection of concepts in a simplified form that are further described in the detailed description below. Therefore, this summary is not intended to identify essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Detailed description is given with reference to the accompanying drawings.

[0007] Figure 1 is an illustration of an environment in an example implementation that is operable to employ the techniques described herein.

[0008] Figure 2 An example of a user interface for outfit curation by generative artificial intelligence is described.

[0009] Figure 3Depicted is an example of another user interface for outfit curation by generative artificial intelligence.

[0010] Figure 4 Depicted is an example of another user interface for outfit curation by generative artificial intelligence.

[0011] Figure 5 Depicted is an example of another user interface for outfit curation by generative artificial intelligence.

[0012] Figure 6 Depicted is an example of another user interface for outfit curation by generative artificial intelligence.

[0013] Figure 7 Depicted is an example of another user interface for outfit curation by generative artificial intelligence.

[0014] Figure 8 Depicted is an example of another user interface for outfit curation by generative artificial intelligence.

[0015] Fig. 9 Depicted is an example of another user interface for outfit curation by generative artificial intelligence.

[0016] Fig.10 Depicted are processes in an example implementation of outfit curation by generative artificial intelligence.

[0017] Fig.11 An example of a system including an example computing device is shown, which is representative of one or more computing systems and / or devices that may implement the various techniques described herein. DETAILED DESCRIPTION

[0018] Overview

[0019] Outfit curation by generative artificial intelligence is described. According to the described technology, an automated outfit curation system uses generative artificial intelligence to automatically curate outfits based on seed clothing items. In one or more implementations, the automatically curated outfits include clothing items available (e.g., listed) on an online marketplace. In one or more implementations, the online marketplace is accessible by a decentralized computing device corresponding to a "client" of the online marketplace, such as a user with an online marketplace account. In at least some cases, the online marketplace generally does not control the actions of users to list items thereon using the functionality of the online marketplace. For example, multiple (e.g., most) users of the online marketplace may not be employed by a company associated with the online marketplace or otherwise similarly controlled by the company. In this way, users of the online marketplace can exert more control over items listed on the online marketplace (e.g., items that users decide to list through the online marketplace) than the company associated with the online marketplace (or its employees or agents).

[0020] Due to this, the inventory of items listed by the online market may be constantly changing. In fact, the next item listed by the user of the online market may be unknown to the online market until the user of the online market provides user input to describe and actually generate the list of the item. As items are added to the online market (e.g., listed for sale) and removed (e.g., purchased or off the shelf), the inventory of the online market and therefore the real-time listing data are constantly changing. For example, many users of the online market can list items that are unique to the online market, making the items "unique" listed by the online market. This is in contrast to the listings of retailers, which usually have more centralized control over their inventory, so the items listed on their websites are known before the items are listed. These retailers plan for the specific items listed. Through the conventional methods adopted by many retailers, buyers purchase multiple identical items and even items of the same size, and the central (or at least controlled) agency makes those planned items listed.

[0021] The ever-changing nature of online marketplaces provides a number of challenges, where decentralized users are able to impact the available inventory at any given time, e.g., by adding unknown items and / or causing various one-off items to be removed. For example, where an online marketplace supports a large number of users (e.g., tens, hundreds, thousands, millions, etc.), it is impossible for a human to track the inventory of listed items via real-time listing data. This is particularly true because there are a large number of item listings, and also because multiple listings for unknown items may be added at unpredictable times. As a result, conventional methods for curating outfits (e.g., methods where humans select clothing items from a known inventory to form an outfit) lack the speed and processing power to keep up with the ever-changing inventory of available clothing items listed on an online marketplace, e.g., due to the decentralized control of items listed on the online marketplace and, in some cases, the unpredictability of items listed by a decentralized group of users.

[0022] Therefore, in order to solve the problems associated with online markets with constantly changing inventory, automated outfit curation technology uses generative artificial intelligence to perform outfit curation. According to the described technology, an automated outfit curation system receives a request to locate clothing items for an outfit that are complementary to a seed clothing item. For example, a request to identify a seed clothing item (e.g., a red t-shirt) is received, and the automated outfit curation system curates an outfit that includes complementary clothing items such as a pair of pants, a pair of shoes, a hat, and accessories that are complementary to the seed clothing item. The automated outfit curation system can receive the request in a variety of different ways. In one or more implementations, a user provides an image of the clothing item to the automated outfit curation system, such as by uploading or taking an image of the clothing item. In other implementations, a request to curate an outfit based on clothing items listed on an online market is received. For example, a user can select clothing items available on an online market and then request a curation of an outfit that includes the selected clothing items.

[0023] Based on the seed clothing item, the automated outfit curation system automatically generates a prompt for input to the generative artificial intelligence. Typically, the automatically generated prompt asks the generative artificial intelligence to create an outfit that includes the seed clothing item and a complementary clothing item available in the online marketplace for the outfit. The prompt includes attributes of the seed clothing item and a predetermined text input. In some cases, the attributes of the seed clothing item are automatically extracted from an image of the clothing item, such as an image provided by a user or an image included in a listing of clothing items on an online platform.

[0024] Providing a prompt to the generative artificial intelligence causes the generative artificial intelligence to initiate a search of the online market to locate complementary clothing items for the outfit that are currently available on the online market. For example, in one or more implementations, the prompt causes the generative artificial intelligence to provide one or more terms for initiating a search query for the online market. The automated outfit curation system can then use the provided terms as input to the online market service and / or application programming interface (API). Therefore, in one or more implementations, the generative artificial intelligence does not directly initiate a search for the online market, but instead provides one or more terms to the automated outfit curation system to search the online market with the services and / or API of the online market. In at least one variant, the generative artificial intelligence directly initiates a search for the online market. In this way, the generative artificial intelligence can create an outfit containing complementary clothing items based on the seed clothing item, and then output a search query containing keywords for the complementary clothing items. The search query is then provided as input to the interface of the online market.

[0025] In response to a search initiated by the generative artificial intelligence, search results are returned that include a list of complementary clothing items for the outfit that are currently available on the online marketplace. For example, the search results include a list of clothing items that are complementary to the seed clothing item and are currently available on the online marketplace. The automated outfit curation system is configured to arrange the list of complementary clothing items for the outfit in a user interface for selection by the user. In one or more implementations, the list is arranged from head to toe, for example, by placing a hat at the top of the user interface, followed by a top, bottoms, and shoes. The user can then select one or more clothing items in order to initiate a transaction for the clothing items to complete the outfit.

[0026] In one or more implementations, the systems and techniques described herein are configured to generate groupings of items based on a seed item rather than a seed clothing item. For example, a seed item such as a piece of furniture may be used by the systems and techniques to generate groups of complementary furniture items, for example, to curate a room or a "space" such as an outdoor space. In this example, the group of complementary furniture items may correspond to other pieces of furniture for the room that match the style of the seed furniture item. As an example, a system may receive an image of a modern sofa for a living room and return a group of furniture items that are complementary or otherwise match the style of the modern sofa, such as a modern coffee table, one or more pieces of modern art, a modern chair, etc. It is worth noting that the ability to generate groups of complementary items based on a seed item is not limited to clothing and furniture, and may include other types of items without departing from the spirit or scope of the described technology.

[0027] In some aspects, the technology described herein relates to a computer-implemented method comprising: generating a prompt for input to a generative artificial intelligence to create an outfit including the seed clothing item based on a seed clothing item, the prompt comprising clothing attributes of the seed clothing item; providing the prompt to the generative artificial intelligence so that the generative artificial intelligence initiates a search of an online marketplace to locate complementary clothing items for the outfit available on the online marketplace; in response to the search initiated by the generative artificial intelligence, receiving search results comprising a list of complementary clothing items for the outfit available on the online marketplace; and arranging the list of complementary clothing items for the outfit in a user interface for selection by a user.

[0028] In some aspects, the techniques described herein relate to a computer-implemented method in which a prompt is automatically generated in response to a request to locate an article of apparel for a costume, the request identifying a seed article of apparel.

[0029] In some aspects, the techniques described herein relate to a computer-implemented method in which the request identifies a style of attire.

[0030] In some aspects, the techniques described herein relate to a computer-implemented method in which a prompt is generated based at least in part on a style of an outfit.

[0031] In some aspects, the techniques described herein relate to a computer-implemented method wherein generating a prompt further comprises: extracting clothing attributes of a seed item of clothing; and incorporating the clothing attributes of the seed item of clothing into preconfigured text of the prompt.

[0032] In some aspects, the techniques described herein relate to a computer-implemented method in which clothing attributes of a seed item of clothing are extracted from an image of the seed item of clothing.

[0033] In some aspects, the techniques described herein relate to a computer-implemented method further comprising displaying one or more interactive elements to facilitate selecting a seed apparel item from images of the seed apparel items.

[0034] In some aspects, the technology described herein relates to a computer-implemented method, further comprising: outputting an interface for capturing an image of the seed apparel item; and receiving input via the interface to initiate capturing of the seed apparel item using a camera device.

[0035] In some aspects, the techniques described herein relate to a computer-implemented method in which clothing attributes of a seed clothing item are extracted from a listing of the seed clothing item on an online marketplace.

[0036] In some aspects, the technology described herein relates to a computer-implemented method in which a generative artificial intelligence initiates a search of an online marketplace by automatically generating a search query to locate articles of clothing for an outfit, wherein the search query is automatically provided to a search interface of the online marketplace.

[0037] In some aspects, the technology described herein relates to a computer-implemented method in which an online marketplace includes a database of listings of apparel items that continuously changes as different listings of apparel items are added and removed from the database.

[0038] In some aspects, the technology described herein relates to a computer-implemented method in which a search result includes a list of complementary clothing items for an outfit that are currently available in a list database.

[0039] In some aspects, the technology described herein relates to a computer-implemented method that also includes generating an avatar wearing the seed item of clothing and the complementary item of clothing.

[0040] In some aspects, the technology described herein relates to a computer-implemented method in which providing a prompt to a generative artificial intelligence causes the generative artificial intelligence to initiate a search of an online marketplace to locate complementary clothing items for a plurality of different outfits available on the online marketplace, wherein each of the plurality of different outfits is associated with a different style.

[0041] In some aspects, the technology described herein relates to a computer-implemented method wherein a seed apparel item corresponds to a category of apparel items, wherein the category of the seed apparel item includes one of headwear, top layers, bottom layers, shoes, or accessories, and wherein the complementary apparel item corresponds to a different category of apparel items that is different from the category of the seed apparel item.

[0042] In some aspects, the technology described herein relates to a system comprising: prompt construction logic configured to generate, based on a seed item of clothing, prompts for input to a generative artificial intelligence to create an outfit including the seed item of clothing, the prompts comprising clothing attributes of the seed item of clothing; the generative artificial intelligence configured to receive the prompts from the prompt construction logic and generate a search query; and an online marketplace configured to receive the search query from the generative artificial intelligence and initiate a search to locate complementary items of clothing for the outfit that are available on the online marketplace;

[0043] In some aspects, the technology described herein relates to a system in which complementary articles of clothing for an outfit are arranged in a user interface for selection by a user.

[0044] In some aspects, the techniques described herein relate to a system in which prompt construction logic is configured to generate a prompt by: extracting clothing attributes of a seed clothing item; and incorporating the clothing attributes of the seed clothing item into preconfigured text of the prompt.

[0045] In some aspects, the techniques described herein relate to a system in which clothing attributes of a seed clothing item are extracted from an image of the seed clothing item.

[0046] In some aspects, the technology described herein relates to one or more computer-readable storage media including computer-executable instructions stored thereon that, in response to execution by one or more processors, perform operations including: generating a prompt for input to a generative artificial intelligence to create an outfit including the seed clothing item based on a seed clothing item, the prompt including clothing attributes of the seed clothing item; providing the prompt to the generative artificial intelligence to cause the generative artificial intelligence to initiate a search of an online marketplace to locate complementary clothing items for the outfit available on the online marketplace; in response to the search initiated by the generative artificial intelligence, receiving search results including a list of complementary clothing items for the outfit available on the online marketplace; and arranging the list of complementary clothing items for the outfit in a user interface for selection by a user.

[0047] In the following discussion, an exemplary environment in which the techniques described herein may be employed is first described. Examples of implementation details and processes that may be performed in the exemplary environment and other environments are then described. The execution of the exemplary processes is not limited to the exemplary environment, and the exemplary environment is not limited to the execution of the exemplary processes.

[0048] Environment Examples

[0049] Figure 1 1 is an illustration of an environment 100 in an example implementation that is operable to employ the techniques described herein. Environment 100 includes a computing device 102, a service provider system 104, and an automated outfit curation system 106. In one or more implementations, computing device 102, service provider system 104, and automated outfit curation system 106 are communicatively coupled to each other via a network 108. One example of network 108 is the Internet, although in various implementations, one or more of computing device 102, service provider system 104, and automated outfit curation system 106 can be communicatively coupled using one or more different connections or different networks.

[0050] Although the automated outfit curation system 106 is depicted in the environment 100 as being separate from the computing device 102 and the service provider system 104, in one or more implementations, the automated outfit curation system 106 in its entirety or in its various portions is implemented at or by the computing device 102 and / or the service provider system 104. In at least one implementation, for example, at least a portion of the automated outfit curation system 106 is implemented by an application 112 of the computing device 102 and / or by using various resources of the computing device 102, such as hardware resources, an operating system, firmware, etc. Alternatively or additionally, at least a portion of the automated outfit curation system 106 is implemented by resources of the service provider system 104 (e.g., server-based storage, processing, etc.). Alternatively or additionally, at least a portion of the automated outfit curation system 106 is implemented using a third-party service, such as a web service platform that provides one or more hardware and / or other computing resources to support services provided by a web service provider.

[0051] The computing device implementing environment 100 can be configured in a variety of ways. For example, the computing device can be configured as a desktop computer, a laptop computer, a mobile device (e.g., assuming a handheld configuration such as a tablet computer or a mobile phone), an Internet of Things (IoT) device, a wearable device (e.g., a smart watch, ring, or smart glasses), an augmented reality / virtual reality (AR / VR) device (e.g., smart glasses), a server, etc. Thus, computing devices range from full-resource devices with large amounts of memory and processor resources to low-resource devices with limited memory and / or processing resources. Additionally, although a computing device is referenced in the singular in the examples discussed below, a computing device also refers to a plurality of different devices, such as with respect to Fig.11 Further described are multiple servers of a server farm for performing operations "on the cloud."

[0052] In at least one implementation, the application 112 supports data communication between the computing device 102 and the service provider system 104 across the network 108. By supporting such data communication, the application 112 provides access to the online marketplace 114 to the respective user of the computing device 102 (as well as users of other computing devices). For example, the computing device 102 receives data from the service provider system 104. Based on the received data, the application 112 causes various systems of the computing device 102 to output a user interface of the online marketplace 114, such as by displaying the user interface via a display device or providing voice-based access to the user interface.

[0053] Through user interaction with computing device 102, application 112 receives user input via one or more user interfaces of online marketplace 114. Examples of such input include, but are not limited to, receiving touch input associated with a portion of a displayed user interface, receiving one or more voice commands, receiving typed input (e.g., via a physical or virtual ("soft") keyboard), receiving mouse or stylus input, and the like. One example of application 112 is a browser that is operable to navigate to a website of online marketplace 114, display pages of the website, and facilitate user interaction with web pages of the website of online marketplace 114. Another example of application 112 is a web-based computer application of online marketplace 114, such as a mobile application or a desktop application. Without departing from the spirit or scope of the technology described herein, application 112 can be configured in different ways, which enables users to interact with their computing devices and, by extension, perform actions on online marketplace 114.

[0054] In one or more implementations, a user registers with the service provider system 104 to obtain a corresponding user account of the online marketplace 114. Such registration may include, for example, providing an email address and establishing a username and password combination. After registering with the service provider system 104, a computing device (e.g., computing device 102) facilitates logging into the user account or otherwise authenticating the user account in various ways, such as by receiving a username and matching password, receiving biometric information (e.g., at least one image of a captured face or captured information of another body part (e.g., a thumb or finger)) that is appropriately matched to stored biometric information associated with the user account, and the like. However, in at least some cases, the user account via which the user accesses the online marketplace 114 may be a guest account that does not require the user to log in or otherwise authenticate an already established account prior to interacting with the online marketplace 114.

[0055] Broadly speaking, the online marketplace 114 is configured to generate listings of items and to make those listings public (e.g., publish them) to one or more computing devices, including the computing device 102. For example, the online marketplace 114 may generate listings of items for sale and expose those listings to computing devices such that users of the computing devices may interact with the listings via a user interface to initiate transactions (e.g., purchases, additions to wish lists, sharing, etc.) related to respective items in the listings. According to the described techniques, the online marketplace 114 is configured to generate listings for one or more types of the following: physical goods or property (e.g., clothing and / or clothing accessories, collectibles, furniture, decorative items, textiles, luxury goods, electronics, real estate, a physical computer-readable storage device having one or more video games stored thereon, etc.), services (e.g., babysitting, dog walking, house cleaning, etc.), digital items that can be downloaded via the network 108 (e.g., digital images, digital music, digital videos), and blockchain-backed assets (e.g., non-fungible tokens (NFTs)), to name a few examples.

[0056] In the illustrated environment 100, the online market 114 includes a storage device 116, which is depicted as maintaining real-time listing data 118. The real-time listing data 118 includes lists of the online market 114, one example of which is list 120. The real-time listing data 118 is depicted with ellipses to indicate that there are more lists than list 120. The storage device 116 can represent one or more databases and / or other types of storage devices capable of storing real-time listing data 118. Examples of storage devices 116 include, but are not limited to, mass storage devices and virtual storage devices. For example, in one or more implementations, the storage device 116 can be virtualized across multiple data centers and / or cloud-based storage devices. The service provider system 104 can implement the online market 114 by using a server that executes storage instructions to deploy various services of the service provider system 104, so that these services perform a large number of calculations that effectively provide the functions described above and below. It should be understood that the online market 114 can include more, less, or different components without departing from the spirit or scope described herein.

[0057] In one or more implementations, the online marketplace 114 may be accessed by decentralized computing devices corresponding to “clients” of the online marketplace 114, e.g., by users with accounts on the online marketplace 114. In at least some cases, the online marketplace 114 generally does not control the actions of users using the functionality of the online marketplace 114 to list items thereon, other than the provision of account and system guardrails implemented by aspects of the online marketplace 114 (e.g., the user interface of the application 112). For example, a plurality (e.g., a majority) of the users of the online marketplace 114 may not be employed by or otherwise similarly controlled by a company associated with the online marketplace 114. In this manner, users of the online marketplace 114 may exert more control over items listed on the online marketplace 114 (e.g., those items that users decide to list through the online marketplace 114) than the online marketplace 114 (or its employees or agents) associated with the company.

[0058] Due to this, the inventory of items listed by the online market 114 may be constantly changing. In fact, the next item listed by the user of the online market 114 may be unknown to the online market 114 until the user of the online market 114 provides user input to describe and actually generate the list of the item. As items are added to the online market 114 (e.g., listed for sale) and removed (e.g., purchased or delisted), the inventory of the online market 114 and therefore the real-time listing data 118 are constantly changing. For example, many users of the online market 114 can list items that are unique to the online market 114, making the items "unique" listed by the online market 114. This is in contrast to the listings of retailers, which usually have more centralized control over their inventory and therefore know the items listed on their websites before the items are listed. These retailers plan for the specific items listed. Through the conventional methods adopted by many retailers, buyers purchase multiple identical items and even items of the same size, and the central (or at least controlled) agency makes those planned items listed.

[0059] The ever-changing nature of the online marketplace 114 provides a number of challenges, where decentralized users are able to impact the available inventory at any given time, such as by adding unknown items and / or causing various one-time items to be removed. For example, where the online marketplace 114 supports a large number of users (e.g., tens, hundreds, thousands, millions, etc.), it is impossible for a human to track the inventory of listed items via the real-time listing data 118. This is particularly true because there are a large number of item listings and because multiple listings for unknown items can be added at unpredictable times. As a result, conventional methods for curating outfits (e.g., methods where humans select clothing items from a known inventory to form an outfit) lack the speed and processing power to keep up with the ever-changing inventory of available clothing items listed on the online marketplace 114, such as due to the decentralized control of the items listed on the online marketplace 114 and, in some cases, the unpredictability of the items listed by a decentralized group of users.

[0060] According to the described techniques, the automated outfit curation system 106 uses generative artificial intelligence 122 for outfit curation. In this example, the automated outfit curation system 106 includes or otherwise accesses generative artificial intelligence 122 and prompt building logic 124. In one or more implementations, the generative artificial intelligence 122 utilizes a class of artificial intelligence techniques and techniques involving the creation of novel and original content, data, and / or artifacts. Unlike traditional artificial intelligence systems that rely on rule-based or deterministic methods, generative artificial intelligence employs algorithms and models that can autonomously produce outputs that are very similar to human-generated content. These algorithms are designed to learn patterns and structures from existing data and then use this learned information to generate new content that is coherent, relevant, and contextually appropriate. Although techniques utilizing generative artificial intelligence are described, in variations, different types of artificial intelligence may be utilized without departing from the spirit or scope of the described techniques.

[0061] In the illustrated environment 100, the prompt construction logic 124 includes a feature description generator 126 with image feature extraction logic 128, and also includes a storage device 130, which is depicted as storing preconfigured text 132. The storage device 130 can represent one or more databases and / or other types of storage devices that are capable of storing preconfigured text 132 and / or other data used by the generative artificial intelligence 122 to perform real-time curation of outfits from clothing items available at a particular time on the online marketplace 114. Examples of storage devices 130 include, but are not limited to, mass storage devices and virtual storage devices. For example, in one or more implementations, the storage device 130 can be virtualized across multiple data centers and / or cloud-based storage devices.

[0062] In one or more implementations, the automated outfit curation system 106 receives a request 134 for locating an item of clothing for an outfit. In at least one variation, the request 134 identifies or otherwise indicates a seed item of clothing 136. By way of example and not limitation, the request 134 includes an image of the seed item of clothing 136, text describing the seed item of clothing 136, and / or a selection of the seed item of clothing 136, such as selecting a list listing the seed item of clothing 136 from the real-time list data 118. The automated outfit curation system 106 uses the seed item of clothing 136 to curate one or more outfits. While the use of only one seed item of clothing is discussed, in at least one variation, multiple seed items of clothing may be identified (e.g., images, text, and / or selections indicating multiple seed items of clothing provided), such that the automated outfit curation system 106 curates one or more outfits based on the multiple seed items of clothing.

[0063] Based on the seed clothing item 136, the prompt construction logic 124 constructs or otherwise generates a prompt 138 for input to the generative artificial intelligence 122 to create an outfit including the seed clothing item 136 and / or based on the seed clothing item 136. According to the described techniques, the prompt 138 includes clothing attributes 140 of the seed clothing item 136.

[0064] In one or more implementations, the prompt construction logic 124 constructs the prompt 138 by combining a portion of the prompt with the clothing attributes 140. For example, the prompt construction logic 124 combines the preconfigured text 132 with the clothing attributes 140, such as one or more text words and / or phrases describing the extracted clothing attributes. As a non-limiting example, the preconfigured text 132 may correspond to a text string such as "Please identify three different styles and create an outfit for each of these styles based on [clothing attributes] using available clothing items from the online marketplace." Additionally, the prompt construction logic 124 may extract clothing attributes 140 of the seed clothing items 136, such as "white," "graphic," "t-shirt." The prompt construction logic 124 may then combine the preconfigured text 132 and the clothing attributes 140 to generate a prompt 138, such as "Please identify three different styles and create an outfit for each of these styles based on a white graphic t-shirt using available clothing items from the online marketplace." In other words, the prompt construction logic 124 may concatenate the text of the preconfigured text 132 with the text corresponding to the clothing attributes 140. The automated outfit curation system 106 provides the prompt 138 as input to the generative artificial intelligence 122. It should be appreciated that the preconfigured text 132 may vary from the example provided immediately above without departing from the spirit or scope of the techniques described herein.

[0065] Additionally or alternatively, the prompt construction logic 124 can form a prompt 138 using a preconfigured partial prompt, but the partial prompt is information of a different type from human-readable text (e.g., a partial feature vector that is not human-understandable text). In such an implementation, clothing attributes 140 can also be extracted and indicated using information different from human-readable text. For example, in one or more variations, clothing attributes 140 can be represented in a feature vector format so that they can be combined with a partial feature vector to form a prompt as a feature vector. Without departing from the spirit or scope of the technology described herein, the prompt 138 can be formatted in various ways for input to the generative artificial intelligence 122.

[0066] In one or more implementations, the feature description generator 126 generates clothing attributes 140 based on the seed clothing item 136. Here, the feature description generator 126 includes an image feature extraction logic 128, which is configured to receive an image depicting a clothing item as input and process the image to output clothing attributes 140 of the clothing item. For example, in one or more implementations, an image of a seed clothing item 136 is provided as input to the image feature extraction logic 128. The image feature extraction logic 128 processes the image of the seed clothing item 136 to extract one or more image features from the image. The image feature extraction logic 128 then generates and outputs clothing attributes 140 (e.g., text labels, text strings, or other suitable information formats) based on the extracted image features. It should be understood that the image feature extraction logic 128 can be configured to include and / or access any of a variety of known techniques (e.g., object recognition, bounding boxes, saliency maps, etc.) to process the image of the seed clothing item 136 to extract clothing attributes 140 of the seed clothing item 136 from the image.

[0067] As described above, the seed apparel item 136 may be identified in other ways, such as via user text input and / or selection of items listed on the online marketplace 114. To this end, the feature description generator 126 may be configured in various variations to determine the clothing attributes 140 of the seed apparel item 136 in different ways based on how the seed apparel item 136 is identified. For example, in the case where the seed apparel item 136 is identified by user input text, the feature description generator 126 may use one or more text-focused techniques (e.g., natural language processing (NLP) techniques) to extract the clothing attributes 140. In the case where the seed apparel item 136 is identified based on the selection of listed apparel items, the feature description generator 126 may obtain one or more of: an image of the corresponding listing, a title of the listing, a description of the listing, a category or underlying data associated with the listing (e.g., metadata of the listing), to name just a few examples. The feature description generator 126 can then use the obtained data as clothing attributes 140 to be incorporated into the prompt 138, and / or the feature description generator 126 can further process the obtained information to extract clothing attributes 140 from the list, such as using a combination of image feature extraction techniques and / or NLP techniques. It should be understood that clothing attributes 140 can be extracted from information in different formats corresponding to the seed clothing item 136 in various ways according to the described techniques.

[0068] After generating the prompt 138, the automated outfit curation system 106 provides the prompt 138 as input to the generative artificial intelligence 122. Providing the prompt 138 as input to the generative artificial intelligence 122 causes the generative artificial intelligence 122 to initiate a search of the online marketplace 114, e.g., to locate complementary clothing items for an outfit that are complementary to the seed clothing item 136 and available on the online marketplace 114. In one or more implementations, the prompt 138 indicates that the seed clothing item 136 is to be included as part of one or more outfits being curated. Alternatively or in addition, the generative artificial intelligence 122 is trained or otherwise programmed so that it incorporates the seed clothing item 136 into the outfits it outputs.

[0069] In one or more implementations, the generative artificial intelligence 122 automatically generates a search query 142 based on receiving the prompt 138, and provides the search query 142 as input to a search interface of the online marketplace 114. By way of example, the generative artificial intelligence 122 generates a plurality of different search queries, such as a plurality of search queries that each correspond to a different determined style of outfit, based on the prompt 138. The generative artificial intelligence 122 may provide the search query 142 to different types of search interfaces of the online marketplace 114. For example, in at least one implementation, the generative artificial intelligence 122 may generate a text search query (e.g., generated using one or more NLP techniques), and provide the text search query as input to a search interface that is or includes an interactive element such as a search bar. Alternatively or additionally, the search interface corresponds to an application programming interface (API), such that at least one of the generative artificial intelligence 122 or the automated outfit curation system 106 configures the search query 142 according to the API, and provides the search query 142 as input to the API of the online marketplace 114. Without departing from the spirit or scope of the described technology, generative artificial intelligence 122 may initiate a search of online marketplace 114 to locate complementary clothing items for an outfit in a variety of ways.

[0070] In response to the search initiated by the generative artificial intelligence 122, the automated outfit curation system 106 receives search results 144 that include or otherwise indicate a list 146 of complementary clothing items on the online marketplace 114. In other words, the search results 144 include a list of real-time listing data 118 for complementary clothing items for an outfit that are available on the online marketplace 114 at the particular time that the outfit is requested (e.g., substantially in real time when the computing device 102 submits the request 134 for a curated outfit).

[0071] In one or more implementations, the complementary clothing item lists 146 are arranged to create outfits 150 for a user interface, wherein the complementary clothing item lists 146 that are combined to form outfits 150 are selectable (e.g., to add to a shopping cart and / or purchase). In at least one implementation, the generative artificial intelligence 122 arranges the complementary clothing item lists 146 into one or more outfits, such as a plurality of outfits specified in the prompt 138. In other words, the generative artificial intelligence 122 arranges the various lists of complementary clothing item lists 146 to produce arranged complementary clothing items 148, wherein each arrangement forms one of the outfits 150.

[0072] In one example, the preconfigured text 132 specifies that clothing items are provided for three outfits, although a different number of outfits may be specified without departing from the spirit or scope of the described technology. For example, the number of outfits specified may be user-selectable and / or adjustable, such as starting from a default number. In at least one implementation, each outfit created by the generative artificial intelligence 122 is a "full" outfit. A non-limiting example of a full outfit includes at least clothing items for tops, bottoms, and footwear, and optionally includes additional items, such as headwear, accessories (e.g., jewelry, watches, bags, glasses, etc.), additional top layers (e.g., vests, jackets, blazers, sweaters, etc.), additional bottom layers (e.g., leggings, skirts, shorts, shorts, etc.), and the like. In fact, without departing from the spirit or scope of the technology described herein, the clothing items that can be combined to create an outfit may correspond to any of various types and / or categories of clothing items.

[0073] The illustrated environment 100 depicts a computing device 102 at two different times, namely, a first time “A” and a second time “B” subsequent to the first time. At the first time, time “A”, the computing device 102 is depicted as displaying a user interface 152 (e.g., a user interface 152 of an application 112), the user interface 152 including an interactive element that can be selected via user input to submit a request to locate an item of clothing for an outfit. At the second time, time “B”, the user interface 152 is depicted as including the formed outfit 150 to include the arranged complementary items of clothing 148, and the user interface 152 also includes an interactive element that can be selected to initiate an action related to the corresponding item of clothing. In at least one implementation, the user interface 152 includes an interactive element for each item of clothing of the arranged complementary items of clothing 148 included in the user interface. Such interactive elements may be selectable to perform actions related only to the respective item of clothing, such as to add the respective item of clothing to an electronic shopping cart or electronic shopping bag of online marketplace 114, to purchase the respective item of clothing, to add the respective item of clothing to a watch list, etc. Alternatively or in addition, the user interface may include interactive elements that are selectable to initiate actions related to more than one item of clothing, such as interactive elements that are selectable to initiate a purchase of all items of clothing forming one of outfits 150 or to perform different actions related to all items of clothing forming one of outfits 150, such as adding the items of clothing of the outfit to an electronic shopping cart or electronic shopping bag.

[0074] The user interface 152 may be configured in a variety of ways to display various items in the outfit 150 and / or the arranged complementary clothing items 148 to the user. In one or more implementations, the user interface 152 may include an avatar, and a virtual version of at least one of the outfits 150 may be generated for display on the avatar. Additionally or alternatively, the user may be able to provide input to deselect and / or select various clothing items from the arranged complementary clothing items 148 included in the outfit 150 to change which of the arranged complementary clothing items 148 are simulated on the avatar. In one or more implementations, the user interface 152 is generated to display the arranged complementary clothing items 148 of the outfit 150 from top to bottom (e.g., head to toe), such that clothing items that are typically worn closer to the top of a person (e.g., hats, necklaces, and tops) are displayed closer to the top of the user interface 152, and clothing items that are typically worn closer to the bottom of a person (e.g., pants, skirts, socks, and footwear) are displayed closer to the bottom of the user interface 152. Alternatively or in addition, user interface 152 may be configured as a grid such that the columns of arranged complementary clothing items 148 correspond to the combinations of clothing items that form an outfit, and such that the rows of arranged complementary clothing items 148 correspond to different options for a portion of an outfit. For example, a row may include images of different tops such that a user may select from different recommended tops in user interface 152 to form an outfit. In one or more implementations, user interface 152 may allow a user to scroll horizontally through individual rows to view different options for a category while other clothing items of the outfit (e.g., other portions of the outfit in a vertical arrangement) remain stationary.

[0075] In one or more implementations, the request 134 identifies a style of the outfit, and the prompt 138 is generated based at least in part on the style. Alternatively or additionally, one or more styles associated with the user submitting the request are accessed (e.g., from user data of the online marketplace 114), and the prompt 138 is generated based at least in part on these one or more styles. For example, the online marketplace 114 may learn one or more styles of the user over time, such as based on one or more of the following: purchase history, browsing history, likes, comments, demographics, social media behavior, images uploaded and / or specified by the user, determined similar users, etc. Thus, in one or more implementations, the automated outfit curation system 106 may curate outfits 150 at least in part using historical style information.

[0076] In one or more implementations, the list of clothing items for the outfit is automatically filtered based on one or more characteristics or preferences of the user. For example, the list of clothing items for the outfit can be filtered to include only clothing items of the correct, determined, or specified size for the user.

[0077] In one or more implementations, the automated outfit curation system 106 generates a plurality of different outfits, each including a seed clothing item. For example, the plurality of different outfits may each be associated with a different style. In some cases, the different styles of the outfits may be based on user input or learned user preferences.

[0078] In one or more implementations, the user interface displays multiple different lists of each clothing item. For example, the user interface may display multiple different lists of similar hats. In some cases, these multiple different lists may be scrolled by the user so that the user may select a preferred clothing item.

[0079] In one or more implementations, the automated outfit curation system 106 automatically generates an avatar of the user wearing the outfit. For example, a three-dimensional avatar of the user wearing the seed clothing item and the complementary clothing item may be generated and displayed via a user interface.

[0080] In one or more implementations, the prompt 138 for the generative artificial intelligence 122 does not include the clothing type of the seed clothing item 136. For example, if the seed clothing item is a red shirt, the prompt 138 requires the generative artificial intelligence 122 to locate clothing items other than the shirt that complements the seed clothing item 136.

[0081] In one or more implementations, an image of the seed apparel item 136 is included in the user interface along with an image of the complementary apparel item.

[0082] In one or more implementations, the generative artificial intelligence 122 initiates a search of multiple different online platforms or markets. For example, the search query 142 generated by the generative artificial intelligence 122 can be provided to the online marketplace 114 and one or more different online marketplaces, one or more online stores, one or more online search engines, and the like.

[0083] Having considered examples of environments, consider now a discussion of some example details of techniques for outfit curation by generative artificial intelligence in accordance with one or more implementations.

[0084] Outfit curation by generative AI

[0085] Figure 2An example 200 of a user interface for outfit curation by generative artificial intelligence is depicted.

[0086] The illustrated example 200 includes a computing device 102 displaying a view item user interface 202. The view item user interface 202 corresponds to a page generated to display a list (e.g., list 120) generated for clothing items listed by the online marketplace 114 and published to, for example, one or more computing devices. In one or more implementations, one or more interactive elements that may be selected to initiate outfit curation using the generative artificial intelligence 122 may be accessible via the view item user interface 202, e.g., such interactive elements are included on the view item user interface 202, and / or a user interface having such elements may be navigated from the view item user interface 202. In one or more implementations, the user interface of the online marketplace 114 and / or the user interface that enables outfit curation by generative artificial intelligence is different from or otherwise distinguishable from the user interfaces discussed herein. Alternatively or additionally, without departing from the spirit or scope of the techniques described herein, the user interfaces used in association with outfit curation by generative artificial intelligence include the user interfaces discussed herein and / or Figures 2 to 9 Any combination of the user interface elements described in .

[0087] Figure 3 An example 300 of another user interface for outfit curation by generative artificial intelligence is depicted.

[0088] The illustrated example 300 includes the computing device 102 displaying a listed item selection user interface 302. The listed item selection user interface 302 includes an interactive element that can be selected to identify a corresponding listed apparel item as a seed apparel item 136.

[0089] Figure 4 An example 400 of another user interface for outfit curation by generative artificial intelligence is depicted.

[0090] The illustrated example 400 includes the computing device 102 displaying a captured item image user interface 402. The captured item image user interface 402 includes an interactive element that can be selected to identify an item of clothing as a seed item of clothing 136 from an image captured by a user and / or from a selected image in an image library or album associated with the user (e.g., accessible via the computing device 102).

[0091] Figure 5 An example 500 of another user interface for outfit curation by generative artificial intelligence is depicted.

[0092] The illustrated example 500 includes a computing device 102 displaying an image capture user interface 502. The image capture user interface 502 includes one or more interactive elements that can be selected to capture an image of a scene, such as a scene including an item of clothing. In one or more implementations, the image capture user interface 502 displays a preview of a portion of the scene by continuously and directly projecting an image formed by a lens of one or more cameras of the computing device 102 onto an image sensor, such that when capture is initiated, the previewed scene is formatted as the captured image. In this way, an image captured based on input to the interactive elements of the image capture user interface 502 can be used as a seed item of clothing 136.

[0093] Figure 6 An example 600 of another user interface for outfit curation by generative artificial intelligence is depicted.

[0094] The illustrated example 600 includes the computing device 102 displaying a progress user interface 602. In one or more implementations, the automated outfit curation system 106 causes the progress user interface 602 to be displayed for a time interval spanning a first time when the request 134 is submitted and a second time when the outfit 150 with the arranged complementary items of clothing 148 is provided back to the computing device 102 in the user interface. For example, the progress user interface 602 may be displayed when the prompt construction logic 124 forms the prompt 138, when the prompt 138 is input to the generative artificial intelligence 122, when the generative artificial intelligence 122 generates the search query 142 and provides it to the online marketplace 114, when the online marketplace 114 searches the real-time listing data 118 for the complementary clothing item list 146, when the search results 144 are sent to the generative artificial intelligence 122, and / or when the generative artificial intelligence 122 arranges the complementary clothing item list 146 into the outfit 150.

[0095] Figure 7 An example 700 of another user interface for outfit curation by generative artificial intelligence is depicted.

[0096] The illustrated example 700 includes a computing device 102 displaying an outfit selection user interface 702. In this example 700, the outfit selection user interface 702 includes three outfits 150 each including arranged complementary clothing items 148 determined by the generative artificial intelligence 122. The outfit selection user interface 702 also includes an interactive element (e.g., "Build an Outfit") that can be selected to navigate to an outfit-specific page to build an outfit, select individual items of an outfit (e.g., for purchase), and / or select multiple items of an outfit (e.g., for purchase). The illustrated example 700 also includes an extended user interface portion 704 that may not be initially visible when the outfit selection user interface 702 is displayed on the computing device 102, but it can be viewed by scrolling down to the extended user interface portion in response to user input. In this example 700, the outfits 150 included in the display are associated with corresponding style names "elegant glamour", "athleisure", and "casual fashion". In one or more implementations, these style names are generated and provided by the generative artificial intelligence 122.

[0097] Figure 8 An example 800 of another user interface for outfit curation by generative artificial intelligence is depicted.

[0098] The illustrated example 800 includes a computing device 102 displaying an item selection user interface 802 for one of the outfits 150. The item selection user interface 802 includes interactive elements displayed on images of complementary clothing items 148 in different arrangements of the outfit 150 that can be selected to perform actions related to the list of depicted items, such as adding the items of the corresponding list to an electronic shopping cart of the online marketplace 114. In this example, each image includes an interactive element that can be selected to add only the corresponding item to the shopping cart, without adding other items to the shopping cart.

[0099] Fig. 9 Depicted is an example 900 of another user interface for outfit curation by generative artificial intelligence.

[0100] The illustrated example 900 includes a computing device 102 displaying an outfit selection user interface 902. The outfit selection user interface 902 includes an interactive element for selecting multiple clothing items in the arranged complementary clothing items 148, and then includes an interactive element for performing a common action related to all of the selected clothing items, such as to purchase all of the selected clothing items. In this way, a user can interact with a single interactive element to purchase multiple clothing items (from different lists) that have been arranged into an outfit in the outfit 150 by the generative artificial intelligence 122.

[0101] Having discussed exemplary details of outfit curation by generative artificial intelligence, we now consider some examples of the process to illustrate additional aspects of the technique.

[0102] Example Process

[0103] This section describes an example of a process for outfit curation by generative artificial intelligence. Various aspects of the process can be implemented in hardware, firmware, or software, or a combination thereof. The processes are shown as a set of blocks that specify operations performed by one or more devices and are not necessarily limited to the order shown for performing the operations by the corresponding blocks.

[0104] Fig.10 Depicted is procedure 1000 in an example implementation of outfit curation by generative artificial intelligence.

[0105] Prompts are generated based on a seed item of clothing for input to a generative artificial intelligence to create an outfit that includes the seed item of clothing (block 1002). According to the described techniques, the prompts include attributes of the seed item of clothing. By way of example, the automated outfit curation system 106 generates prompts 138 for input to the generative artificial intelligence 122 to create an outfit 150 that includes the seed item of clothing 136 based on a request to identify the seed item of clothing 136. The prompts 138 include clothing attributes 140 of the seed item of clothing 136.

[0106] The prompt is provided to the generative artificial intelligence to initiate a search of the online marketplace to locate complementary clothing items for the outfit 150 that are available on the online marketplace (block 1004). By way of example, the prompt construction logic 124 of the automated outfit curation system 106 provides the prompt 138 to the generative artificial intelligence 122 to initiate a search of the online marketplace 114 to locate complementary clothing items for the outfit 150 that are available on the online marketplace 114.

[0107] In response to the search initiated by the generative artificial intelligence, a search result is received that includes a list of complementary clothing items for the outfit available on the online marketplace (block 1006). By way of example, in response to the search initiated by the generative artificial intelligence 122, a search result 144 is received that includes a list 146 of complementary clothing items for the outfit 150 available on the online marketplace 114.

[0108] A list of complementary clothing items for the outfit is arranged in a user interface for selection by the user (block 1008). By way of example, the arranged complementary clothing items 148 are output via one or more of the outfit selection user interface 702, the item selection user interface 802, or the outfit selection user interface 902 for selection by the user.

[0109] Having described examples of processes according to one or more implementations, consider now examples of systems and devices that may be used to implement the various techniques described herein.

[0110] Example Systems and Devices

[0111] Fig.11 An example of a system is shown generally at 1100, which includes an example of a computing device 1102, which represents one or more computing systems and / or devices that may implement the various techniques described herein. This is illustrated by the inclusion of application 112 and automated outfit curation system 106. Computing device 1102 may be, for example, a server of a service provider, a device associated with a client (e.g., a client device), a system on a chip, and / or any other suitable computing device or computing system.

[0112] The example computing device 1102 as shown includes a processing system 1104, one or more computer-readable media 1106, and one or more I / O interfaces 1108 that are communicatively coupled to each other. Although not shown, the computing device 1102 may also include a system bus or other data and command transmission system that couples the various components to each other. The system bus may include any one of different bus structures or a combination of different bus structures, such as a memory bus or memory controller, a peripheral bus, a universal serial bus, and / or a processor or local bus that utilizes any one of a variety of bus architectures. Various other examples are also contemplated, such as control lines and data lines.

[0113] Processing system 1104 represents a function for performing one or more operations using hardware. Therefore, processing system 1104 is shown as including hardware elements 1110 that can be configured as processors, functional blocks, etc. This can include an implementation in the form of hardware as a dedicated integrated circuit or other logic device formed using one or more semiconductors. Hardware elements 1110 are not limited by the materials from which they are formed or the processing mechanisms employed therein. For example, a processor can be composed of semiconductors and / or transistors (e.g., electronic integrated circuits (ICs)). In such a case, the processor executable instructions can be electronic executable instructions.

[0114] Computer-readable media 1106 is shown to include memory / storage 1112. Memory / storage 1112 represents the capacity of a memory / storage associated with one or more computer-readable media. Memory / storage 1112 may include volatile media (e.g., random access memory (RAM)) and / or non-volatile media (e.g., read-only memory (ROM), flash memory, optical disks, magnetic disks, etc.). Memory / storage 1112 may include fixed media (e.g., RAM, ROM, fixed hard drives, etc.) and removable media (e.g., flash memory, removable hard drives, optical disks, etc.). As further described below, computer-readable media 1106 may be configured in various other ways.

[0115] The input / output interface 1108 represents functionality that enables a user to input commands and information to the computing device 1102, and also enables information to be presented to the user and / or other components or devices using various input / output devices. Examples of input devices include a keyboard, a cursor control device (e.g., a mouse), a microphone, a scanner, touch functionality (e.g., a capacitive or other sensor configured to detect physical touch), a camera (e.g., which may employ visible or invisible wavelengths such as infrared frequencies to identify movement as gestures that do not involve touch), etc. Examples of output devices include a display device (e.g., a monitor or projector), a speaker, a printer, a network card, a tactile response device, etc. Thus, as further described below, the computing device 1102 may be configured in various ways to support user interaction.

[0116] Various techniques may be described herein in the general context of software, hardware elements, or program modules. Typically, such modules include routines, programs, objects, elements, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The terms "module," "function," and "component" as used herein generally represent software, firmware, hardware, or a combination thereof. The features of the techniques described herein are platform-independent, meaning that the techniques can be implemented on a variety of commercial computing platforms with a variety of processors.

[0117] An implementation of the described modules and techniques may be stored on or transmitted across some form of computer-readable media. Computer-readable media may include a variety of media that may be accessed by the computing device 1102. By way of example and not limitation, computer-readable media may include “computer-readable storage media” and “computer-readable signal media.”

[0118] "Computer-readable storage media" may refer to media and / or devices that enable persistent and / or non-transient storage of information, as compared to signal transmission alone, carrier waves, or the signal itself. Therefore, computer-readable storage media refers to non-signal bearing media. Computer-readable storage media include hardware such as volatile and non-volatile, removable and non-removable media and / or storage devices implemented in a method or technology suitable for storing information such as computer-readable instructions, data structures, program modules, logic elements / circuits, or other data. Examples of computer-readable storage media may include, but are not limited to: RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical storage device, hard disk, cassette, magnetic tape, magnetic disk storage device or other magnetic storage device, or other storage device, tangible media, or an article suitable for storing the desired information and accessible by a computer.

[0119] "Computer-readable signal media" may refer to signal-bearing media that is configured to send instructions to the hardware of the computing device 1102, for example, via a network. Signal media may typically embody computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave, a data signal, or other transport mechanism. Signal media also include any information delivery media. The term "modulated data signal" refers to a signal that has one or more of its characteristics set or changed in a manner that encodes information in the signal. By way of example and not limitation, communication media include wired media such as a wired network or direct wired connection and wireless media such as acoustic, RF, infrared and other wireless media.

[0120] As previously described, hardware elements 1110 and computer-readable media 1106 represent modules, programmable device logic, and / or fixed device logic that can be adopted in some embodiments to implement at least some aspects of the technology described herein (e.g., execute one or more instructions) implemented in hardware form. Hardware can include components of integrated circuits or components of systems on a chip, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), complex programmable logic devices (CPLDs), and other implementations in silicon or other hardware. In this case, the hardware can be operated as a processing device that performs program tasks defined by instructions and / or logic embodied by the hardware, and hardware for storing execution instructions, such as the previously described computer-readable storage medium.

[0121] The aforementioned combination may also be used to implement the various techniques described herein. Therefore, software, hardware or executable modules may be implemented as one or more instructions and / or logic embodied in some form of computer-readable storage medium, and / or implemented by one or more hardware elements 1110. Computing device 1102 may be configured to implement specific instructions and / or functions corresponding to software modules and / or hardware modules. Therefore, the implementation of a module that can be executed as software by computing device 1102 may be implemented at least partially in hardware, for example, by using a computer-readable storage medium and / or a hardware element 1110 of a processing system 1104. Instructions and / or functions may be executed / operated by one or more articles (e.g., one or more computing devices 1102 and / or processing systems 1104) to implement the techniques, modules and examples described herein.

[0122] The techniques described herein can be supported by various configurations of computing device 1102 and are not limited to the specific examples of the techniques described herein. The functionality can also be implemented in whole or in part on a "cloud" 1114 using a distributed system, such as via platform 1116, as described below.

[0123] The cloud 1114 includes and / or represents a platform 1116 for resources 1118. The platform 1116 abstracts the underlying functionality of the hardware (e.g., servers) and software resources of the cloud 1114. The resources 1118 may include applications and / or data that may be utilized when performing computer processing on a server remote from the computing device 1102. The resources 1118 may also include services provided over the Internet and / or over a subscriber network (e.g., a cellular or Wi-Fi network).

[0124] The platform 1116 can abstract resources and functionality to connect the computing device 1102 with other computing devices. The platform 1116 can also be used to abstract the scale of resources to provide a corresponding level of scale to the demand encountered for resources 1118 (which are implemented via the platform 1116). Therefore, in an interconnected device embodiment, the implementation of the functionality described herein can be distributed throughout the system 1100. For example, the functionality can be implemented in part on the computing device 1102 and can be implemented via the platform 1116 that abstracts the functionality of the cloud 1114.

[0125] in conclusion

[0126] Although the systems and techniques have been described in language specific to structural features and / or methodological acts, it should be understood that the systems and techniques defined in the appended claims are not necessarily limited to the specific features or acts described. Rather, these specific features and acts are disclosed as example forms of implementing the claimed subject matter.

Claims

1. A computer-implemented method comprising: generating a prompt based on a seed item of clothing, the prompt for input into a generative artificial intelligence to create an outfit including the seed item of clothing, the prompt including clothing attributes of the seed item of clothing; providing the prompt to the generative artificial intelligence to cause the generative artificial intelligence to initiate a search of an online marketplace to locate complementary clothing items for the outfit that are available on the online marketplace; In response to the search initiated by the generative artificial intelligence, receiving search results including a listing of the complementary clothing items for the outfit available on the online marketplace; and The list of the complementary clothing items for the outfit is arranged in a user interface for selection by a user.

2. The computer-implemented method of claim 1 , wherein: The prompt is automatically generated in response to a request to locate an article of clothing for the outfit, the request identifying the seed article of clothing.

3. The computer-implemented method of claim 2, wherein: The request identifies a style of the attire.

4. The computer-implemented method of claim 3, wherein: The prompt is generated based at least in part on the style of the attire.

5. The computer-implemented method of claim 1 , wherein: Generating the prompt further includes: extracting the clothing attributes of the seed clothing item; and The apparel attributes of the seed apparel item are incorporated into preconfigured text of the prompt.

6. The computer-implemented method of claim 5, wherein: The clothing attributes of the seed clothing item are extracted from the image of the seed clothing item.

7. The computer-implemented method of claim 6, further comprising displaying one or more interactive elements to facilitate selection of the seed apparel item from the image of the seed apparel item.

8. The computer-implemented method of claim 6, further comprising: outputting an interface for capturing the image of the seed clothing item; as well as An input is received via the interface to initiate photographing of the seed clothing item using a camera device.

9. The computer-implemented method of claim 5, wherein: The apparel attributes of the seed apparel item are extracted from a listing of the seed apparel item on the online marketplace.

10. The computer-implemented method of claim 1, wherein: The generative artificial intelligence initiates the search of the online marketplace by automatically generating a search query to locate articles of clothing for the outfit, wherein the search query is automatically provided to a search interface of the online marketplace.

11. The computer-implemented method of claim 1 , wherein: The online marketplace includes a database of listings for clothing items that continuously changes as different listings for clothing items are added and removed from the database.

12. The computer-implemented method of claim 11, wherein: The search results include a listing of the complementary clothing items for the outfit that are currently available in the listing database.

13. The computer-implemented method of claim 1, further comprising generating an avatar wearing the seed item of clothing and the supplemental item of clothing.

14. The computer-implemented method of claim 1, wherein: Providing the prompt to the generative artificial intelligence causes the generative artificial intelligence to initiate a search of an online marketplace to locate complementary clothing items available on the online marketplace for a plurality of different outfits, wherein each of the plurality of different outfits is associated with a different style.

15. The computer-implemented method of claim 1, wherein: The seed apparel item corresponds to a category of apparel items, wherein the category of the seed apparel item includes one of headwear, top layers, bottom layers, shoes, or accessories, and wherein the supplemental apparel item corresponds to a different category of apparel items that is different than the category of the seed apparel item.

16. A system comprising: prompt construction logic configured to generate prompts based on a seed item of clothing, the prompts for input into a generative artificial intelligence to create an outfit including the seed item of clothing, the prompts including garment attributes of the seed item of clothing; a generative artificial intelligence configured to receive the prompt from the prompt building logic and generate a search query; as well as An online marketplace configured to receive the search query from the generative artificial intelligence and to initiate a search to locate complementary clothing items for the outfit that are available on the online marketplace.

17. The system of claim 16, wherein: The complementary clothing items for the outfit are arranged in a user interface for selection by a user.

18. The system of claim 16, wherein: The prompt construction logic is configured to generate the prompt by: extracting the clothing attributes of the seed clothing item; and The apparel attributes of the seed apparel item are incorporated into preconfigured text of the prompt.

19. The system of claim 18, wherein: The clothing attributes of the seed clothing item are extracted from the image of the seed clothing item.

20. One or more computer-readable storage media comprising computer-executable instructions stored thereon, the computer-executable instructions, in response to execution by one or more processors, performing operations comprising: generating a prompt based on a seed item of clothing, the prompt for input into a generative artificial intelligence to create an outfit including the seed item of clothing, the prompt including clothing attributes of the seed item of clothing; providing the prompt to the generative artificial intelligence to cause the generative artificial intelligence to initiate a search of an online marketplace to locate complementary clothing items for the outfit that are available on the online marketplace; In response to the search initiated by the generative artificial intelligence, receiving search results including a listing of the complementary clothing items for the outfit available on the online marketplace; and The list of the complementary clothing items for the outfit is arranged in a user interface for selection by a user.

Images