Abstract: An online system customizes documents for a particular context, user, or set of users. The online system receives an image of a physical document and extracts components, such as text, titles, items and their metadata, from the physical document. The online system may apply rules to the metadata for one or more items to determine whether to modify at least a portion of the metadata. The online system also applies a model to generate an affinity score for a context or a user and each component of the document. If the score for a component is below a threshold, the online system prompts a generative model to generate replacement content for the component. Subsequently, the online system applies the model to the generated replacement content and updates the document with the generated replacement content for the component if the score of the generated replacement content is higher.

Abstract: An online system applies a visual language model and an optical character recognition model to a received image to generate descriptive information about unknown items in the image. The online system prompts a generative model with the descriptive information about unknown items in the image to separate the descriptive information into different bins each corresponding to a different unknown item in the image. For each unknown item detected in the image, the online system generates a target embedding from its descriptive information and performs a nearest neighbor search on an item catalog including embeddings for various items to find a set of candidate embeddings matching the target embedding. The online system retrieves item attributes of candidate items each corresponding to a candidate embedding of the set and prompts the generative model with this information to rank candidate items for the unknown item in the image.

Abstract: An online system performs flyer quality assurance monitoring to identify and remedy errors in flyers. The online system generates a prompt for a large language machine-learning model (LLM) to verify the flyer's accuracy. The prompt includes a portion of the flyer and a query to identify errors in that portion. The online system provides the prompt to a model serving system for execution by the LLM. The online system receives, from the model serving system, a response indicating error(s) identified in the portion of the flyer. Responsive to receiving identifying the errors, the online system performs remedial measure(s) to correct the identified error(s). Remedial measures may include correcting associations to items in an item catalog, modifying textual information or image data in the flyer, etc. The online system transmits the corrected flyer to client device(s) for presentation to user(s) of the online system.

Abstract: An online system that maintains a website, such as a white-labeled website, designed by an entity retrieves a set of contextual data associated with the website, in which the set of contextual data includes information describing the entity, one or more elements of the website, or a historical performance of the website. The online system generates a prompt including the set of contextual data and a request for a set of recommendations for improving a performance of the website by updating a set of elements of the website. The online system provides the prompt to a large language model to obtain an output and extracts, from the output, the set of recommendations for improving the performance of the website. The online system sends the set of recommendations to a computing system associated with the entity.

Abstract: An online system uses a trained machine-learning model for efficient packing of items. Upon receiving, from a device of an agent or a device of a source via a network, a signal indicating that a set of items are ready for packing, the online system applies the machine-learning model to identify, based at least in part on input data, a packing order for one or more items of the set of items. Based on the identified packing order for the one or more items, the online system generates a packing interface signal. The online system sends the packing interface signal, wherein sending the packing interface signal causes the one or more items to be packed according to the identified packing order. This process is repeated until it is confirmed that all items from the set of items were packed.

Abstract: An online system customizes documents for a particular context, user, or set of users. The online system receives an image of a physical document and extracts components, such as text, titles, items and their metadata, from the physical document. The online system may apply rules to the metadata for one or more items to determine whether to modify at least a portion of the metadata. The online system also applies a model to generate an affinity score for a context or a user and each component of the document. If the score for a component is below a threshold, the online system prompts a generative model to generate replacement content for the component. Subsequently, the online system applies the model to the generated replacement content and updates the document with the generated replacement content for the component if the score of the generated replacement content is higher.

Abstract: Operations include: receiving a first request for a first dataset of a plurality of datasets stored in a particular database instance; obtaining an encrypted version of the first dataset; obtaining an encrypted version of the first DEK; requesting decryption of the encrypted version of the first DEK; receiving a decrypted version of the first DEK; applying the first DEK to the encrypted version of the first dataset to obtain a decrypted version of the first dataset; and transmitting the decrypted version of the first dataset. The first dataset is encrypted by a first DEK associated with a first tenant. A second dataset is encrypted by a second DEK associated with a second tenant. The decrypted version of the first DEK is generated by applying a first MEK of the first tenant to the encrypted version of the first DEK.

Abstract: An online system displays an ordering interface, and responsive to receiving a request from a client device to place an order including one or more items to be collected from a retailer location, the system retrieves data associated with each item. The system accesses and applies a machine-learning model to predict a likelihood of each item being a predictable availability item having at least a threshold measure of fluctuating availability throughout the day at the retailer location based on data associated with a corresponding item. The system identifies a set of predictable availability items based on the predicted likelihood(s) and predicts an availability of each identified predictable availability item at the retailer location during a future timeframe. The system then updates the ordering interface to describe the predicted availability of each predictable availability item at the retailer location during the future timeframe.

Abstract: Operations include: receiving a first request for a first dataset of a plurality of datasets stored in a particular database instance; obtaining an encrypted version of the first dataset; obtaining an encrypted version of the first DEK; requesting decryption of the encrypted version of the first DEK; receiving a decrypted version of the first DEK; applying the first DEK to the encrypted version of the first dataset to obtain a decrypted version of the first dataset; and transmitting the decrypted version of the first dataset. The first dataset is encrypted by a first DEK associated with a first tenant. A second dataset is encrypted by a second DEK associated with a second tenant. The decrypted version of the first DEK is generated by applying a first MEK of the first tenant to the encrypted version of the first DEK.

Abstract: An online system generates digital flyers using a generative model. The online system receives, from a client device, a request to generate a digital flyer. The request includes one or more design conditions for the digital flyer. For example, the design conditions may specify one or more cornerstone items, a theme, a template flyer, other target characteristics, etc. The online system further accesses an item catalog storing item data. The online system generates a query for a generative model including a prompt to generate the digital flyer, the one or more design conditions, and item data accessed from the item catalog. The online system provides the query to a model serving system, which executes the generative model with the query to return a batch of one or more digital flyers. The online system provides a first digital flyer in the batch of one or more digital flyers for presentation.

Abstract: An energy transmission system comprising a pole, at least one wire, a sensing system coupled to the pole for monitoring pole temperature, dynamic pole loading, external impact on the pole, vibration of the pole, and wires that are downed, at least one line sensor coupled to the wire and at least one powered data integrator. The sensing system comprises at least one dynamic pole loading sensor and a three-dimensional accelerometer. The dynamic pole loading sensor can be coupled to the lower portion of the pole above ground level but not more than 10 feet above ground level. Optionally there are two dynamic pole loading sensors, the first sensor having a longitudinal axis parallel to a longitudinal axis of the pole, and the second sensor having a longitudinal axis perpendicular to the longitudinal axis of the pole.

Abstract: An energy transmission system comprising a pole, at least one wire, a sensing system coupled to the pole for monitoring pole temperature, dynamic pole loading, external impact on the pole, vibration of the pole, and wires that are downed, at least one line sensor coupled to the wire and at least one powered data integrator. The sensing system comprises at least one dynamic pole loading sensor and a three-dimensional accelerometer. The dynamic pole loading sensor can be coupled to the lower portion of the pole above ground level but not more than 10 feet above ground level. Optionally there are two dynamic pole loading sensors, the first sensor having a longitudinal axis parallel to a longitudinal axis of the pole, and the second sensor having a longitudinal axis perpendicular to the longitudinal axis of the pole.

Abstract: A method for locating an anomaly in a distribution circuit including utility power lines includes coupling a radio frequency energy source to the utility power lines, transmitting chirped radio frequency signals into the utility power lines, receiving and digitizing/analyzing signals reflected from the chirped signals by impedance mismatches caused by components and features of the distribution circuit, and generating from the digitized signals of multiple sets of the chirped radio frequency signals a reference data set identifying at least the locations of at least some of the components and features of the distribution circuit. Later sets of the chirped radio frequency signals are transmitted into the utility power lines and signals reflected from the sets of chirped signals are received and digitized and are compared with the reference data set to determine if there are anomalies on the distribution circuit.

Abstract: A method of playing a poker type game uses a standard deck of 52 playing cards. The deck includes four suits and thirteen sets of four ranging from two through ace. The game is played by dealing four cards to each of six or seven players' locations and four cards to the dealer location on a specially adapted gaming table. Each player and the dealer then separate their cards into three hands, a high hand, a medium hand and a low hand, in accordance with a predetermined hierarchy or ranking of the hands, or at the preference of the player. In order to win, each of the players must beat the dealer two out of three hands or all three hands. For example, a player's high and medium hands must beat the dealer's high and medium hands, medium and low hands must beat the dealer's medium and low hands, or high and low hands must beat the dealer's high and low hands, or the player must beat all three high, medium, and low hands. For the dealer to win, he or she must beat a player two out of the three or all three hands.