Abstract: A method of facilitating content selection includes generating benchmark queries for a particular category. Generating the benchmark queries includes applying a text prompt as input to a language model trained on a knowledge base. The text prompt requests search queries indicative of user interest in the particular category. The method also includes selecting, responsive to new search queries entered by users, content items associated with the particular category for delivery to client devices of the users. Selecting the content items includes determining whether the new search queries correspond to the particular category at least in part by comparing the new search queries to a query set that includes the benchmark queries.

Abstract: A method, apparatus, non-transitory computer readable medium, and system for image processing include obtaining a text prompt. The method, apparatus, non-transitory computer readable medium, and system further include selecting an image generation model based on a length of the text prompt. In one aspect, the image generation model is trained to generate images using training data including text prompts below a threshold length. An aspect further includes generating, using the selected image generation model, a synthetic image based on the text prompt. In one aspect, the synthetic image includes an element described by the text prompt.

Abstract: A method of monitoring a particle size distribution (PSD) is provided. At least a partially coherent pupil-engineered beam may be produced. A plurality of particles having a particle size distribution (PSD) may be illuminated by the pupil-engineered beam to produce scattered light. The scattered light may be captured by a pixelated photoelectric detector, thereby creating a raw speckled image. An intensity correlation of the raw speckled image may be computed. The intensity correlation may be provided to an inverse module. The inverse module may be configured to determine the PSD based on the intensity correlation. The PSD may be obtained from the inverse module.

Abstract: A method of monitoring a particle size distribution (PSD) is provided. A plurality of particles having a particle size distribution (PSD) may be illuminated by an at least partially coherent beam to produce scattered light. The scattered light may be captured by a pixelated photoelectric detector, thereby creating an ensemble of raw speckled images. Based on the ensemble of the raw speckled images. an ensemble-averaged intensity correlation may be computed. The ensemble-averaged intensity correlation may be provided to an inverse module. The inverse module may be configured to determine the PSD based on the ensemble-averaged intensity correlation. The particle size distribution may be obtained from the inverse module.

Abstract: The present application discloses a method, system, and computer system for managing data using keys. The method includes receiving a request to access data stored within a tenant database associated with a tenant, wherein the data is encrypted based at least in part on a tenant service encryption key (TSEK) corresponding to the tenant database, determining a wrapper key used in connection with encrypting the TSEK based at least in part on a TSEK metadata stored in association with the TSEK, determining a top-level key used in connection with encrypting the wrapper key based at least in part on wrapper key metadata stored in association with the encrypted version of the wrapper key, obtaining the data stored within the tenant database, comprising decrypting at least part of the data based at least in part on (i) the TSEK, (ii) the wrapper key, and (iii) the top-level key, and providing the data in response to the request. The TSEK metadata is stored in the tenant database.

Abstract: An electric motor is particularly suited for a radiator fan. The motor has a motor carrier with an electronics compartment for motor electronics. The electronics compartment has an electronics compartment base and a side wall projecting in the vertical direction relative to the electronics compartment base. An electronics compartment cover closes the electronics compartment. The electronics compartment cover has a channel-like receptacle for a free end of the side wall. The receptacle has an outer wall arranged on the outside of the side wall. A lug extends from the outer wall, in particular from a free end of the outer wall, counter to the vertical direction. The lug has a lug base portion and a snap-in element arranged thereon for a snap-in connection to a snap-in nose of the motor carrier.

Abstract: Technology is disclosed herein for enhanced similarity search. In an implementation, a search environment includes one or more computing hardware, software, and/or firmware components in support of enhanced similarity search. The one or more components identify a modality for a similarity search with respect to a query object. The components generate an embedding for the query object based on the modality and based on connections between the query object and neighboring nodes in a graph. The embedding for the query object provides the basis for the search for similar objects.

Abstract: Provided is a system and method whereby a bank customer can engage a remote second party in a financial deal which is specific to a specific bank, all within the operational framework of an existing mobile phone messaging application which is other than the Specific Bank app. In certain circumstances, an embodiment of the present system and method entails two related elements: (i) having installed on the bank customer's mobile phone a Specific Bank mobile application which the bank customer normally uses for direct financial dealings with Specific Bank; and also (ii) having a Specific Bank extension application, installed on the mobile phone. The Specific Bank extension application (hereinafter, “extension app”) enables the provision of Specific Bank mobile application services from within the messaging application, so that the bank customer can engage in financial dealings with the second party via the messaging application.

Abstract: Various embodiments use a neural network to analyze images for aspects that characterize the images, to present locations of those aspects on the images, and, additionally, to permit a user to interact with those locations on the images. For example, a user may interact with a visual cue over one of those locations to modify, refine, or filter the results of a visual search, performed on a publication corpus, that uses an input image (e.g., one captured using a mobile device) as a search query.

Abstract: Systems and methods for image processing are configured. Embodiments of the present disclosure identify target style attributes and target structure attributes for a composite image; generate a matrix of composite feature tokens based on the target style attributes and the target structure attributes, wherein subsequent feature tokens of the matrix of composite feature tokens are sequentially generated based on previous feature tokens of the matrix of composite feature tokens according to a linear ordering of the matrix of composite feature tokens; and generate the composite image based on the matrix of composite feature tokens, wherein the composite image includes the target style attributes and the target structure attributes.

Abstract: A method, apparatus, non-transitory computer readable media, and system for image generation include obtaining an input text prompt and an indication of a level of a target characteristic, where the target characteristic comprises a characteristic used to train an image generation model. Some embodiments generate an augmented text prompt comprising the input text and an objective text corresponding to the level of the target characteristic. Some embodiments generate, using the image generation model, an image based on the augmented text prompt, where the image depicts content of the input text prompt and has the level of the target characteristic.

Abstract: A method, apparatus, non-transitory computer readable medium, and system for generating synthetic images depicting an image element with a target composition include obtaining a content input and a composition input. The content input indicates an image element and the composition input indicates a target composition of the image element. Embodiments then encode the composition input to obtain a composition embedding representing the target composition. Subsequently, embodiments generate, using an image generation model, a synthetic image based on the content input and the composition embedding. The synthetic image depicts the image element with the target composition.

Abstract: A method, apparatus, non-transitory computer readable medium, and system for media processing includes obtaining a variation parameter and a number of variations, identifying a first variation input and a second variation input for the variation parameter, and obtaining a first media content item and a second media content item based on the first variation input and the second variation input, respectively. The first media content item and the second media content item vary from each other with respect to the variation parameter. The method, apparatus, non-transitory computer readable medium, and system for media processing further includes displaying the first media content item and the second media content item in a grid comprising a grid size based on the number of variations.

Abstract: A method, apparatus, non-transitory computer readable medium, and system for image generation include obtaining a text prompt and a conditioning attribute. The text prompt is encoded to obtain a text embedding. The conditioning attribute is encoded to obtain an attribute embedding. Then a synthesized image is generated using an image generation model based on the text embedding and the attribute embedding. The synthesized image has the conditioning attribute and depicts an element of the text prompt.

Abstract: A method, apparatus, non-transitory computer readable medium, and system for media processing includes obtaining a text prompt and a style input, where the text prompt describes image content and the style input describes an image style, generating a text embedding based on the text prompt, where the text embedding represents the image content, generating a style embedding based on the style input, where the style embedding represents the image style, and generating a synthetic image based on the text embedding and the style embedding, where the text embedding is provided to the image generation model at a first step and the style embedding is provided to the image generation model at a second step after the first step.

Abstract: A method, apparatus, non-transitory computer readable medium, and system for image generation include encoding a text prompt to obtain a text embedding. An image prompt is encoded to obtain an image embedding. Cross-attention is performed on the text embedding and then on the image embedding to obtain a text attention output and an image attention output, respectively. A synthesized image is generated based on the text attention output and the image attention output.

Abstract: Systems, methods, and computer program products for identifying a candidate product in an electronic marketplace based on a visual comparison between candidate product image visual content and input query image visual content. Embodiments generate and store descriptive image signatures from candidate product images or selected portions of such images. A subsequently calculated visual similarity measure serves as a visual search result score for the candidate product in comparison to an input query image. Any number of images of any number of candidate products may be analyzed, such as for items available for sale in an online marketplace. Image analysis results are stored in a database and made available for subsequent automated on-demand visual comparisons to an input query image. The embodiments enable substantially real time visual based product searching of a potentially vast catalog of items.

Abstract: Embodiments are disclosed for machine learning-based generation of recommended layouts. The method includes receiving a set of design elements for performing generative layout recommendation. A number of each type of design element from the set of design elements is determined. A set of recommended layouts are generated using a trained generative layout model and the number and type of design elements. The set of recommended layouts are output.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating digital images by conditioning a diffusion neural network with input prompts. In particular, in one or more embodiments, the disclosed systems generate, utilizing a reverse diffusion model, an image noise representation from a first image prompt. Additionally, in some embodiments, the disclosed systems generate, utilizing a diffusion neural network conditioned with a first vector representation of the first image prompt, a first denoised image representation from the image noise representation. Moreover, in some embodiments, the disclosed systems generate, utilizing the diffusion neural network conditioned with a second vector representation of a second image prompt, a second denoised image representation from the image noise representation.

Abstract: Systems and methods for image processing are described. Embodiments of the present disclosure identify a plurality of candidate concepts in a knowledge graph (KG) that correspond to an image tag of an image; generate an image embedding of the image using a multi-modal encoder; generate a concept embedding for each of the plurality of candidate concepts using the multi-modal encoder; select a matching concept from the plurality of candidate concepts based on the image embedding and the concept embedding; and generate association data between the image and the matching concept.