Abstract: Improved multi-modal machine learning networks integrate computer vision systems with language models. In certain embodiments, a computer vision system analyzes at least one image to generate a computer vision output. The language model generates an output based, at least in part, on a consideration of the computer vision output. The outputs of the language model can be generated by jointly considering textual information learned by the language model and visual content extracted by the computer vision system, thereby significantly improving the accuracy, breadth, and comprehensiveness of the outputs.

Abstract: This disclosure relates to improved techniques for personalizing vehicle routes and operator sessions using pre-trained machine learning language models. In certain embodiments, a language model is trained on operator interaction data to learn operator route preferences for vehicle operators. These learned operator route preferences can be leveraged to optimize and personalize vehicle routes and operator sessions in various ways. Other embodiments are disclosed herein as well.

Abstract: This disclosure relates to improved techniques for personalizing vehicle routes and operator sessions using pre-trained machine learning language models. In certain embodiments, a language model is trained on operator interaction data to learn operator route preferences for vehicle operators. These learned operator route preferences can be leveraged to optimize and personalize vehicle routes and operator sessions in various ways. Other embodiments are disclosed herein as well.

Abstract: Improved multi-modal machine learning networks integrate computer vision systems with language models. In certain embodiments, a computer vision system analyzes at least one image to generate a computer vision output. The language model generates an output based, at least in part, on a consideration of the computer vision output. The outputs of the language model can be generated by jointly considering textual information learned by the language model and visual content extracted by the computer vision system, thereby significantly improving the accuracy, breadth, and comprehensiveness of the outputs.

Abstract: This disclosure relates to artificial intelligence (AI) and machine learning networks for predicting or determining demand metrics across multiple channels. An analytics platform can receive channel events from multiple channels corresponding to geographic areas, and channel features related to demand conditions in the channels can be extracted from the channel events. During a training phase, the channel features can be accumulated into one or more training datasets for training one or more demand prediction models. The one or more demand prediction models can be trained to predict or determine demand metrics for each of the channels. The demand metrics can indicate or predict demand conditions based on the current conditions in the channels and/or based on future, predicted conditions in the channels. Other embodiments are disclosed herein as well.

Abstract: This disclosure relates to decentralized computing networks, architectures and techniques for collecting, analyzing, and processing data over multiple channels. A decentralized computing network comprises a plurality of computing nodes, each of which is dedicated to analyzing and processing events for a particular channel corresponding to a geographic region. Each node of the decentralized computing network can operate independently to process channel analysis data for a corresponding channel. The decentralized configuration of the nodes enables efficient processing of data collected over large geographic areas, increases the reliability of the system, and facilitates easy scaling of the system. Other embodiments are disclosed herein as well.

Abstract: Improved techniques for adapting the look, feel, and/or behavior of a mobile application based on user attributes, location, and/or environment in which it is used are described herein. A triggering condition is determined to be satisfied between a hand-held device and a beacon. Based on the triggering condition being satisfied, one or more application settings are applied to an adaptive application, where these settings are associated with the beacon. Additionally, in response to fetching or acquiring an application skin that is associated with the beacon, the application skin is also applied to the adaptive application.

Abstract: A crypto-currency based value interoperability computing system for transferring closed-loop value within an accrued value system using crypto-currency is provided. The cyrpto currency based system may include an integration tier operable for managing mobile wallet sessions while maintaining integrity of the session. Notification services may also form part of the system as does a service connector layer. The system may further employ business process services and a payment handler service. Security and authorization services may also provided. The system may further employ use of a mobile device configured to run a cyrpto-currency based value interoperability system application that may involve transfers from and to stored value funding accounts with associated permissions and validation. The system may further include tokenizing the stored value funding account through a toke service provider who may employ a token management system.

Abstract: Embodiments are directed to providing targeted messages using a plurality of communication channels and to providing targeted messages to mobile devices. In one scenario, a computer system instantiates a multi-channel communication service that is configured to provide different targeted messages using multiple different communication channels. The computer system further determines that a targeted message is to be provided to a specified user through a first communication channel, and provides the targeted message through the first communication channel. The computer system also determines that the targeted message is to be provided to the specified user through a second, additional communication channel, and provides the targeted message through the second, different communication channel. The messages may include any type of content including text, pictures, videos, links or other content.