Abstract: A server comprises a communications module; a processor coupled with the communications module; and a memory coupled to the processor and storing processor-executable instructions which, when executed by the processor, configure the processor to receive, via the communications module and from a computing device, a signal representing a request to perform an operation from a user; determine that the user does not have a persistent account; and when it is determined that the user does not have a persistent account: obtain, via the communications module and from a digital identity network, a signal including verified identity data of the user; generate a temporary data record and associate the temporary data record with the verified identity data of the user; receive a value transfer based on the requested operation and store the received value in the temporary data record; and perform the operation using the stored value in the temporary data record.

Abstract: Systems and methods are described that employ machine learning models to optimize database management. Machine learning models may be utilized to decide whether a new database record needs to be created (e.g., to avoid duplicates) and to decide what record to create. For example, candidate database records potentially matching a received database record may be identified in a local database, and a respective probability of each candidate database record matching the received record is output by a match machine learning model. A list of statistical scores is generated based on the respective probabilities and is input to an in-database machine learning model to calculate the probability that the received database record already exists in the local database.

Abstract: A computerized data transfer system allows data transfers to be initiated over a network between senders and recipients. Individual senders initiate data transfers over the network by selecting a recipient from a list at a sender device. The system includes a data store of sender specific recipients, a data transfer history data store of past transfers; and a master participant data store storing profiles of recipients for which transfers can be initiated. The system includes a computing device that for selected senders, retrieves entries of the data store of sender specific recipients, master participant data store and data transfer history data store; generates a predicted transfer profile for each recipient for the sender, based on past data transfers and the master participant data store to identify deviations therefrom; and updates the data store of sender specific recipients for the selected sender to update entries for recipients associated with identified deviations.

Abstract: The present disclosure contains embodiments of an apparatus, system and method designed to facilitate learning or efficient multitasking involving movement and solar energy where users' movement devices process or respond to different stimuli to facilitate users moving while learning, working, or participating in a simulation. In some embodiments this may be accomplished with the aid of a circular treadmill, spherical walkway, or combinable modular trackpads that may be linked to allow a user to lay the apparatus in a path suited for a plurality of environments. The embodiments of the disclosure involve the user moving while processing information and receiving feedback, assistance related to that movement, processing, or any combination thereof while combining the motion of the movement device with the feedback loop sent from sensor relays a user may receive an optimal experience for learning while moving. Some embodiments make efficient use of solar energy for classroom education management.

Abstract: Systems and associated methods are described for providing content recommendations. The system selects a first plurality of subsets of content categories, each subset of content categories comprising a first number of content categories. The subsets are assigned reward scores based on content popularity and duplication. The subset are then iteratively modified to increase the rewards scores. If the reward scores are still low, the process is repeated by selecting a second plurality of subsets of content categories, each subset of content categories comprising a second number of content categories, different from first number.

Abstract: The general field of the disclosure herein relates to the design of one or more health related monitoring or maintenance devices. These devices may include but are not limited to devices that monitor and/or maintain the health of users or devices that monitor and/or maintain the health of assets. The devices include oral cleaning devices for maintaining and monitoring the oral health of users, clothing for monitoring the health and fitness of users and charging pads which may monitor the health or assets being charged. Sensors may be integrated in these devices including but not limited to IMUs, thermocouples or oral cleaning devices, IMUs in clothing like shoes or wrist bands, or timers or charging sensors in magnetic surfaces which may cause one or more objects and/or other magnetic surfaces to float when a desired function is achieved.

Abstract: A computerized data transfer system allows data transfers to be initiated over a network between senders and recipients. Individual senders initiate data transfers over the network by selecting a recipient from a list at a sender device. The system includes a data store of sender specific recipients, a data transfer history data store of past transfers; and a master participant data store storing profiles of recipients for which transfers can be initiated. The system includes a computing device that for selected senders, retrieves entries of the data store of sender specific recipients, master participant data store and data transfer history data store; generates a predicted transfer profile for each recipient for the sender, based on past data transfers and the master participant data store to identify deviations therefrom; and updates the data store of sender specific recipients for the selected sender to update entries for recipients associated with identified deviations.

Abstract: Systems and associated methods are described for providing content recommendations. The system receives a plurality of sets of range values, each of which corresponds to a respective one of a plurality of parameters for recommending the content. The system selects different values within each of the plurality of sets of range values over time and provides a plurality of content recommendations to users based on the selected different values. The system then analyze users' behavior in response to the provided plurality of content recommendations. The system further updates at least one set of range values based on the analyzed users' behavior.

Abstract: Systems and methods are described that employ machine learning models to optimize database management. Machine learning models may be utilized to decide whether a new database record needs to be created (e.g., to avoid duplicates) and to decide what record to create. For example, a match machine learning model may be used in combination with an in-database machine learning model and an out-of-policy machine learning model. The match machine learning model may calculate a probability that a newly received database record individually matches respective candidate database records identified in a local database, the in-database machine learning model may calculate a probability that the received database record is in the local database, and the out-of-policy machine learning model may be used to calculate a probability that the newly received database record complies with inclusion rules of the local database.

Abstract: Methods and systems for presenting contextually relevant push content when a user is passively engaged with an application are described herein. The system detects that the user is engaged with an application on a device and monitors the user's level of engagement with the application. If the system determines that the user is passively engaged, the system prepares to insert push content into the current output. The system identifies a region on the current output into which to insert push content, for example a region unoccupied by content or a particular object. The system identifies a context of the current output and selects a push content item based on the context of the current output. Then, the system inserts the push content item into the empty region on the current output.

Abstract: Systems and associated methods are described for providing content recommendations. The system accesses a plurality of recommendation algorithms and assigns a plurality of weight values to each prediction algorithm. Then, the system generates a set of candidate weight combinations, such that each candidate combination includes a weight value assigned to each prediction algorithm. Then requests for content items are received over a predetermined period of time. For each combination, the system generates a set of recommended content items and an evaluation metric that is based on matches with requests. Afterwards, the system replaces a candidate combination that resulted in a generation of a lowest evaluation metric. The aforementioned steps are repeated until the evaluation metrics stop improving. Then display identifiers are displayed for a set of recommended content items generated for a candidate combination with the highest evaluation metric.

Abstract: Systems and associated methods are described for providing content recommendations. The system receives a plurality of sets of range values, each of which corresponds to a respective one of a plurality of parameters for recommending the content. The system selects different values within each of the plurality of sets of range values over time and provides a plurality of content recommendations to users based on the selected different values. The system then analyze users' behavior in response to the provided plurality of content recommendations. The system further updates at least one set of range values based on the analyzed users' behavior.

Abstract: Systems and methods are described for selecting content item identifiers for display. The system may identify a set of content items that are likely to be requested in the future based on a history of content item requests. The system then selects a first plurality of content categories using a category selection neural net and selects a first set of recommended content items for the first plurality of content categories. The system increases a reward score for the first plurality of content categories based on receiving a request for a content item that is included in the first set of recommended content items. The system also decreases the reward score for the first plurality of content categories based on determining that the requested content item is included in the set of content items that are likely to be requested in the future. The neural net is trained based on the reward score of the first plurality of content categories to reinforce reward score maximization.

Abstract: In one embodiment, a system includes an interface and a communicatively coupled processor. The interface is configured to receive first future location information of a first user and receive second future location information of a second user. The processor is configured to determine that the first and second future location information each correspond to a future location and determine that a characteristic related to the first user corresponds to a preference related to the second user. In response to these determinations, the processor is configured to cause information to be presented to the second user, the information to be presented to the second user comprising the future location and that the first user and the second user have the future location in common.

Abstract: A server comprises a communications module; a processor coupled with the communications module; and a memory coupled to the processor and storing processor-executable instructions which, when executed by the processor, configure the processor to receive, via the communications module and from a computing device, a signal representing a request to perform an operation from a user; determine that the user does not have a persistent account; and when it is determined that the user does not have a persistent account: obtain, via the communications module and from a digital identity network, a signal including verified identity data of the user; generate a temporary data record and associate the temporary data record with the verified identity data of the user; receive a value transfer based on the requested operation and store the received value in the temporary data record; and perform the operation using the stored value in the temporary data record.

Abstract: Methods and systems for presenting contextually relevant push content when a user is passively engaged with an application are described herein. The system detects that the user is engaged with an application on a device and monitors the user's level of engagement with the application. If the system determines that the user is passively engaged, the system prepares to insert push content into the current output. The system identifies a region on the current output into which to insert push content, for example a region unoccupied by content or a particular object. The system identifies a context of the current output and selects a push content item based on the context of the current output. Then, the system inserts the push content item into the empty region on the current output.

Abstract: Systems and associated methods are described for providing content recommendations. The system accesses a plurality of recommendation algorithms and assigns a plurality of weight values to each prediction algorithm. Then, the system generates a set of candidate weight combinations, such that each candidate combination includes a weight value assigned to each prediction algorithm. Then requests for content items are received over a predetermined period of time. For each combination, the system generates a set of recommended content items and an evaluation metric that is based on matches with requests. Afterwards, the system replaces a candidate combination that resulted in a generation of a lowest evaluation metric. The aforementioned steps are repeated until the evaluation metrics stop improving. Then display identifiers are displayed for a set of recommended content items generated for a candidate combination with the highest evaluation metric.

Abstract: Systems and methods are described for selecting content item identifiers for display. The system may identify a set of content items that are likely to be requested in the future based on a history of content item requests. The system then selects a first plurality of content categories using a category selection neural net and selects a first set of recommended content items for the first plurality of content categories. The system increases a reward score for the first plurality of content categories based on receiving a request for a content item that is included in the first set of recommended content items. The system also decreases the reward score for the first plurality of content categories based on determining that the requested content item is included in the set of content items that are likely to be requested in the future. The neural net is trained based on the reward score of the first plurality of content categories to reinforce reward score maximization.

Abstract: In one embodiment, a system includes an interface and a communicatively coupled processor. The interface is configured to receive first future location information of a first user and receive second future location information of a second user. The processor is configured to determine that the first and second future location information each correspond to a future location and determine that a characteristic related to the first user corresponds to a preference related to the second user. In response to these determinations, the processor is configured to cause information to be presented to the second user, the information to be presented to the second user comprising the future location and that the first user and the second user have the future location in common.

Abstract: An apparatus includes an interface and a processor. The interface sends and receives data over a network. The processor uses the interface to transmit a first media file to a device of a user. The first media file presents a first choice between at least two options. The processor uses the interface to receive from the user a first selection in response to the first choice. In response to receiving the first selection, the processor transmits a second media file to the device. The second media file presents a second choice between at least two options. The processor uses the interface to receive from the user a second selection in response to the second choice. The processor identifies, based in part on the first selection and the second selection, a second user as potentially compatible with the user and transmits to the user a profile of the second user.