Abstract: The complexity of implementing machine learning models in software systems can be reduced using an abstraction system. The abstraction system functions as an intermediary between a machine learning service and a client process. The abstraction system provides a unified API by which the client process can submit client requests targeting a machine learning model and also abstracts the complexity of configuring model requests in the appropriate form for a particular machine learning service and model. The abstraction system also provides a standard mechanism for delivering results to the client process in an actionable format and for tracking outcomes of any actions that the results trigger. The abstraction system therefore greatly simplifies the process of employing machine learning models within a software system.

Abstract: An off-chain abstraction mechanism for distributing NFTs in an educational or similar environment is provided. The off-chain abstraction mechanism abstracts away required knowledge and activities that are directly involved in the issuance to and collection of NFTs both on and off-chain by students thereby allowing teachers to focus simply on rewarding desired behaviors by issuing digital coins to students. Teachers can distribute digital coins to students that are grouped into teams as part of a game or challenge. Digital coins can be associated with a point value that can be added to a team's score during a round of the game. A school administrator can declare a round complete at which point the teams' scores can be used to identify one or more winning teams. Off-chain NFTs can then be distributed to the students of a winning team. The students may view their off-chain NFTs at any time. Also, students desiring to do so may redeem an off-chain NFT for a matching on-chain NFT.

Abstract: A system for off-chain management, distribution and auditing of decentralized cryptocurrency is provided. The system enables an organization to mint off-chain, centrally controlled tokens for internal distribution within the organization. The system allows these tokens to be assigned an underlying value in a cryptocurrency and to be associated with distribution rules and withdrawal rules. When a token is distributed to an employee, it does not guarantee that the employee will receive the underlying value in the cryptocurrency. Instead, the token represents the employee's ability to withdraw up to the assigned underlying value in the cryptocurrency, which the organization can approve, adjust or deny. When the organization approves an employee's withdrawal of a token's underlying value, the system can manage the distribution of the token's underlying value to the employee's cryptocurrency wallet and can provide functionality for tracking, reporting and auditing such transactions.

Abstract: As part of implementing a recognition and reward system, a communications platform can employ a unique set of data structures, APIs and a rules engine that abstract the definition of rewards from the definition of rules for determining when the rewards should be made available. Accordingly, boosters may interface directly with the communications platform to offer rewards to participants but need not be aware of or involved in the process of defining the rules that will be used to distribute the rewards. Likewise, administrators may interface directly with the communications platform to define rules for making rewards available without needing to be aware of the rewards themselves. In this way, a communications platform can integrate boosters and their rewards into a recognition and rewards system without requiring tight coupling between the rules for determining when rewards should be made available and the rewards themselves.

Abstract: A platform can be employed to implement a personalized learning system that is simple to use, streamlined and scalable thereby enabling such systems to be seamlessly implemented in any learning environment. The platform can be implemented in a client-server environment in which a server or servers maintain a number of data structures which can be used to define students, assignments, classes, flashcards, videos, and learning standards definitions, among many others. A number of backend processes, websites, and web APIs can be configured to allow users to access the content of these data structures as well as to create new entries in these data structures to thereby facilitate the implementation of a personalized learning system that incorporates automation and machine learning in a school, workplace or other learning environment.

Abstract: As part of implementing a recognition and reward system, a communications platform can employ a unique set of data structures, APIs and a rules engine that abstract the definition of rewards from the definition of rules for determining when the rewards should be made available. Accordingly, boosters may interface directly with the communications platform to offer rewards to participants but need not be aware of or involved in the process of defining the rules that will be used to distribute the rewards. Likewise, administrators may interface directly with the communications platform to define rules for making rewards available without needing to be aware of the rewards themselves. In this way, a communications platform can integrate boosters and their rewards into a recognition and rewards system without requiring tight coupling between the rules for determining when rewards should be made available and the rewards themselves.

Abstract: The complexity of implementing machine learning models in software systems can be reduced using an abstraction system. The abstraction system functions as an intermediary between a machine learning service and a client process. The abstraction system provides a unified API by which the client process can submit client requests targeting a machine learning model and also abstracts the complexity of configuring model requests in the appropriate form for a particular machine learning service and model. The abstraction system also provides a standard mechanism for delivering results to the client process in an actionable format and for tracking outcomes of any actions that the results trigger. The abstraction system therefore greatly simplifies the process of employing machine learning models within a software system.

Abstract: A platform can be employed to implement a personalized learning system that is simple to use, streamlined and scalable thereby enabling such systems to be seamlessly implemented in any learning environment. The platform can be implemented in a client-server environment in which a server or servers maintain a number of data structures which can be used to define students, assignments, classes, flashcards, videos, and learning standards definitions, among many others. A number of backend processes, websites, and web APIs can be configured to allow users to access the content of these data structures as well as to create new entries in these data structures to thereby facilitate the implementation of a personalized learning system that incorporates automation and machine learning in a school, workplace or other learning environment.

Abstract: A platform can be employed to implement a personalized learning system that is simple to use, streamlined and scalable thereby enabling such systems to be seamlessly implemented in any learning environment. The platform can be implemented in a client-server environment in which a server or servers maintain a number of data structures which can be used to define students, assignments, classes, flashcards, videos, and learning standards definitions, among many others. A number of backend processes, websites, and web APIs can be configured to allow users to access the content of these data structures as well as to create new entries in these data structures to thereby facilitate the implementation of a personalized learning system that incorporates automation and machine learning in a school, workplace or other learning environment.