Abstract: A processor may incorporate one or more keys in a media. The one or more keys may each be associated with a specific instance and the one or more keys may be included in a blockchain. The processor may identify that a first specific instance has been encountered. The processor may provide a first key associated with the first specific instance. The processor may determine to allow access to content of the media.

Abstract: A processor may identify that a computing device is below a power threshold. The processor may generate a charge request. The charge request may include metrics associated with a requested power exchange. The processor may send the charge request to a decentralized exchange. The decentralized exchange may include the computing device and at least two other devices. The processor may receive respective charging proposals from the at least two other devices. The processor may select one of the respective charging proposals.

Abstract: A node in a blockchain network may send an operation for geometrically fractionalizing an non-fungible token (NFT) into geometric shards to a blockchain network. The geometric fractionalization associates each geometric shard with a specific part of the NFT. The node may also record, on distributed ledger of the blockchain network, the fractionalization of the NFT and the association between each geometric shard with the specific part of the NFT.

Abstract: According to one embodiment, a method, computer system, and computer program product for fractional NFT trading marketplace is provided. The embodiment may include minting a mark associated with an entity as a fractional non-fungible token by a creator with ownership or authority over the mark, where the creator establishes a plurality of parameters during the minting. The embodiment may also include processing one or more purchases of one or more fractions of the fractional non-fungible token by one or more individuals from the creator. The embodiment may further include monitoring data associated with the fractional non-fungible token for criteria that triggers an event. The embodiment may also include in response to the criteria being present, executing the event.

Abstract: Dynamically adjusting, using artificial intelligence (AI), sensors and models of an autonomous roaming robotic device, which includes receiving data regarding an asset at a computer of a roaming robotic device from sensors on the robotic device. The robotic device identifies an asset at a location using the sensors, and the robotic device has instructions, received from a control system, to inspect the location or items at the location. The data is analyzed using the computer of the robotic device, and the analysis includes using historical data for the asset. An AI model is loaded using the computer of the robotic device, based on the identification of the asset. A sensor is selected using the computer of the robotic device, for conducting an inspection of the asset based on the analysis of the data and the AI model.

Abstract: Embodiments relate to a system, program product, and method for smart contract implementation and management. A request for resources is modeled and a reservation of resources is captured in a first computation model interface. A provision of services is modeled as a second computation model interface. Compatibility of the first and second computation model interfaces is verified. Input and output actions are synchronized between the first and second computation model interfaces responsive to the compatibility verification. A smart contract is composed as a third computation model interface to model negotiation of contractual terms, including the captured resources with the provision of services. The composed smart contract is recorded in an operatively coupled immutable venue.

Abstract: A system for optimizing deployment of a machine learning workload is provided. A computer device receives information pertaining to a machine learning workload to be processed for a client device. The computer device determines a machine learning model for the workload and a processing location for the workload based, at least in part, on the information. The computer device generates a request to process the workload at the determined processing location utilizing the determined machine learning model.

Abstract: Methods and systems for training a neural network include transmitting a first request for training data. The request includes information about the training data and information about a neural network model. A reduced training dataset is received that includes minimal viable data, responsive to the first request. A reconstructed training dataset is generated from the reduced training dataset. The model is trained using the reconstructed dataset.

Abstract: Approaches presented herein enable securely paying for stored energy. More specifically, a request to purchase a quantity of energy is sent. One or more offers to provide the quantity of energy are received. An offer of the one or more offers is accepted, where the accepted offer is made by a provider. The quantity of energy is received from the provider, and a payment based upon the accepted offer is sent to the provider.

Abstract: Techniques for securing peer-to-peer off-line transactions such as mobile device energy sharing through the use of broadcast encryption are provided. In one aspect, a method for securing transactions includes: encrypting the transactions in a digital wallet of a user in a digital network (e.g., a blockchain network) in a manner whereby the user can encrypt but cannot decrypt the transactions, and other users in the digital network can decrypt but cannot encrypt the transactions, thereby requiring the user to reveal all or none of the transactions in the digital wallet of the user since the user does not know which of the transactions is which, wherein one or more of the transactions are conducted off-line without users having a connection to the digital network.

Abstract: A processor may identify that a computing device is below a power threshold. The processor may generate a charge request. The charge request may include metrics associated with a requested power exchange. The processor may send the charge request to a decentralized exchange. The decentralized exchange may include the computing device and at least two other devices. The processor may receive respective charging proposals from the at least two other devices. The processor may select one of the respective charging proposals.

Abstract: A processor may incorporate one or more keys in a media. The one or more keys may each be associated with a specific instance and the one or more keys may be included in a blockchain. The processor may identify that a first specific instance has been encountered. The processor may provide a first key associated with the first specific instance. The processor may determine to allow access to content of the media.

Abstract: An example operation may include one or more of splitting a session key into a plurality of partial shares, distributing the plurality partial shares to a plurality of content providers, respectively, where each content provider receives a different partial share of the session key, encrypting a stream of media content based on the session key, and transmitting the encrypted stream of digital content to a user device which has one or more partial shares among the plurality of partial shares.

Abstract: An example operation may include one or more of splitting a session key into a plurality of partial shares, distributing the plurality partial shares to a plurality of content providers, respectively, where each content provider receives a different partial share of the session key, encrypting a stream of media content based on the session key, and transmitting the encrypted stream of digital content to a user device which has one or more partial shares among the plurality of partial shares.

Abstract: An example operation may include one or more of receiving, by a validation node, a copy request from a user node over a blockchain network, the request contains a copy token, invoking, by the validation node, a smart contract associated with the copy token to verify the copy token, in response to a verification, generating, by the validation node, media copy keys for generation of a Blu-ray copy, and recording, by the validation node, the copy token on a ledger of the blockchain network to indicate that the copy token is spent.

Abstract: Embodiments relate to a system, program product, and method for smart contract implementation and management. A request for resources is modeled and a reservation of resources is captured in a first computation model interface. A provision of services is modeled as a second computation model interface. Compatibility of the first and second computation model interfaces is verified. Input and output actions are synchronized between the first and second computation model interfaces responsive to the compatibility verification. A smart contract is composed as a third computation model interface to model negotiation of contractual terms, including the captured resources with the provision of services. The composed smart contract is recorded in an operatively coupled immutable venue.

Abstract: A computer-implemented method according to one embodiment includes receiving a data object from a first application running on a computing device, a unique identifier (ID) of the data object assigned by the first application, and an access permission for the data object from the first application. The computer-implemented method also includes storing the data object, the unique ID, and the access permission in a data repository in a data distributor layer on the computing device. The computer-implemented method also includes receiving, at an access controller layer of the computing device, a request for the data object from a second application, the request including the unique ID, and retrieving, by the access controller layer, the data object from the data distributor layer using the unique ID in response to the request. The computer-implemented method includes providing, by the access controller layer, the data object to the second application.

Abstract: An example operation may include one or more of receiving, by a validation node, a copy request from a user node over a blockchain network, the request contains a copy token, invoking, by the validation node, a smart contract associated with the copy token to verify the copy token, in response to a verification, generating, by the validation node, media copy keys for generation of a Blu-ray copy, and recording, by the validation node, the copy token on a ledger of the blockchain network to indicate that the copy token is spent.

Abstract: A computer-implemented method according to one embodiment includes receiving a data object from a first application running on a computing device, a unique identifier (ID) of the data object assigned by the first application, and an access permission for the data object from the first application. The computer-implemented method also includes storing the data object, the unique ID, and the access permission in a data repository in a data distributor layer on the computing device. The computer-implemented method also includes receiving, at an access controller layer of the computing device, a request for the data object from a second application, the request including the unique ID, and retrieving, by the access controller layer, the data object from the data distributor layer using the unique ID in response to the request. The computer-implemented method includes providing, by the access controller layer, the data object to the second application.