A non-transitory processor-readable medium stores instructions to be executed by a processor. The instructions cause the processor to receive a first trained machine learning model that generates a transcription based on a document. The instructions cause the processor to execute the first trained machine learning model and a second trained machine learning model to generate a refined transcription based on the transcription. The instructions cause the processor to execute a quality assurance program to generate a transcription score based on the document and the transcription. The instructions cause the processor to execute the quality assurance program to generate a refined transcription score based on the refined transcription and at least one of the document or the transcription. The at least one refined transcription score indicates an automation performance better than an automation performance for the at least one transcription score.

A non-transitory processor-readable medium stores instructions to be executed by a processor. The instructions cause the processor to receive a first trained machine learning model that generates a transcription based on a document. The instructions cause the processor to execute the first trained machine learning model and a second trained machine learning model to generate a refined transcription based on the transcription. The instructions cause the processor to execute a quality assurance program to generate a transcription score based on the document and the transcription. The instructions cause the processor to execute the quality assurance program to generate a refined transcription score based on the refined transcription and at least one of the document or the transcription. The at least one refined transcription score indicates an automation performance better than an automation performance for the at least one transcription score.

Various embodiments are described herein for a system and method for determining a medical product dispensed by a pharmacy. The method involves operating a processor to: receive, from a computing device, image data depicting at least a portion of a prescription document issued by the pharmacy; extract, from the image data, a pharmacy identifier for identifying the pharmacy associated with issuing the prescription document; select, based on the pharmacy identifier, at least one parsing method for parsing prescription documents issued by the pharmacy identified by the pharmacy identifier; and apply the selected parsing method to the image data to determine a medical product identifier for identifying the medical product dispensed by the pharmacy.

An apparatus to perform functions on media content items comprises a camera, a communication interface, and a selector input device. The selector input device is communicatively coupled to the camera and the communication interface and has a function setting. In response to detecting activation of the selector input device, the camera captures a media content item and the communication interface transmits the media content item to the server for function processing. The selector input device can be a rotary wheel. To select the function setting from the plurality of settings, the user can rotate the rotary wheel to a function setting and press the rotary wheel. Other embodiments are described herein.

An apparatus to perform functions on media content items comprises a camera, a communication interface, and a selector input device. The selector input device is communicatively coupled to the camera and the communication interface and has a function setting. In response to detecting activation of the selector input device, the camera captures a media content item and the communication interface transmits the media content item to the server for function processing. The selector input device can be a rotary wheel. To select the function setting from the plurality of settings, the user can rotate the rotary wheel to a function setting and press the rotary wheel. Other embodiments are described herein.

A method and apparatus comprising generating a dynamic personalized webpage is disclosed. At least two webpages are loaded in a fashion that is hidden from the user. Content from the at least two webpages is extracted based on classification “of interest” by an artificial intelligence algorithm. A dynamic personalized webpage comprising extracted content is then generated and displayed to the user. In the preferred embodiment, the user's dynamic personalized webpage will be filled with advertisements tailored to the user and the user would receive at least some revenue from advertisements.

The disclosed embodiments describe methods, systems, and apparatuses for determining user intent. A method is disclosed comprising obtaining a session text of a user; calculating, by the processor, a feature vector based on the session text; determining probabilities that the session text belongs to a plurality of intent labels, the probabilities calculated using a multi-level hierarchal intent classification model, the intent labels assigned to levels in the multi-level hierarchal intent classification model; and assigning a user intent to the session text based on the probabilities.

A third party item listing management system usable for verification of third party items to be included on a retailer website includes an application programming interface and an item verification pipeline. The application programming interface is accessible by a plurality of third parties and is configured to receive item data associated with one or more items. The item verification pipeline is configured to receive the item data and call an item validation pipeline, the item validation pipeline includes a plurality of item validation stages including a field verification. At the field verification stage, data is extracted from at least one of an item image or text associated with the item. The data extracted is compared to item data obtained from an independent verification source to confirm the accuracy of the item data provided by the third party.

Systems and methods for digital identity verification are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for digital identify verification may include: (1) receiving, from a user electronic device or at a website, an image of an identity document for a user, the identity document comprising an image of the user; (2) processing the identity document with at least one business-specific rule; (3) extracting identity information from the identity document; (4) determining a match rate of the image of the user on the identity document to a captured image; (5) assigning a verification score to the user based on extracted identity information and the match rate; and (6) publishing the verification score to at least one system.

Implementations relate to causing a command to be executed based on an image. In some implementations, a computer-implemented method includes obtaining and programmatically analyzing an image to determine suggested actions. The method causes a user interface to be displayed that includes user interface elements corresponding to default actions, and to suggested actions that are determined based on analyzing the image. The method receives user input indicative of selection of a particular action from the default actions and the suggested actions. The method causes a command to be executed by a computing device for the particular action that was selected.