Abstract: Systems, methods, and corresponding computer-readable media for multi-modal hierarchical semantic search of electronic documents. Systems in accordance with the disclosure comprise search engine controllers, any desired numbers of search engine interface controllers, and persistent data stores accessible by the search engine controllers. The controllers are configured to parse searchable document data sets to extract document object data sets. Each document object data set can represent textual and/or image feature of the document. For each document object data sets the controller generates at least one enriched document object data set, and forms at least one of a document graph or index. In response to search requests, the search controller compares document graphs or indexes to identify the most similar documents.

Abstract: Examples of neural networks trained for multiple tasks are described herein. In some examples, a method may include determining a feature vector using a first portion of a neural network. In some examples, the neural network is trained for multiple tasks. Some examples of the method may include transmitting the feature vector to a remote device. In some examples, the remote device is to perform one of the multiple tasks using a second portion of the neural network.

Abstract: A method includes receiving, with a computing device, a configuration file and a client request to apply a machine learning model to a set of data from a sensor. The method includes performing, with the computing device, preprocessing on the set of data from the sensor based on the configuration file to generate preprocessed data. The method includes sending, with the computing device, a call to a model server to apply the machine learning model to the preprocessed data.

Abstract: A system may comprise a processor to execute an application, a keystroke analyzer module to determine a frequency with which each key on a keyboard is utilized during execution of the application, and a key illumination module to illuminate the keys on the keyboard with an illumination pattern that visually distinguishes a first subset of keys on the keyboard from a second subset of keys on the keyboard.

Abstract: An application-classification and peripheral device settings (APDS) system may comprise a categorization subsystem to capture descriptive information about an application, analyze the descriptive information, determine a classification of the application, and assign the application to an application category that includes applications that each have a similar classification. The system may also include a peripheral device configuration subsystem to identify a peripheral device setting from the application category and apply the peripheral device setting to an operating configuration of the application.

Abstract: A method includes receiving, with a computing device, a first client request from a first client that identifies a machine learning model and a sensor. The method includes sending, with the computing device, a call to a server to apply the identified machine learning model to a set of data from the identified sensor, in response to the first client request. The method includes receiving, with the computing device, a second client request from a second client that identifies a same machine learning model and sensor as the first client request. The method includes sending, with the computing device, response data from the identified machine learning model to both the first client and the second client without sending an additional call to the server in response to the second client request.

Abstract: A method includes receiving, with a computing device, a configuration file and a client request to apply a machine learning model to a set of data from a sensor. The method includes performing, with the computing device, preprocessing on the set of data from the sensor based on the configuration file to generate preprocessed data. The method includes sending, with the computing device, a call to a model server to apply the machine learning model to the preprocessed data.