Various aspects of the disclosure relate to using a verifiable and distributed encoding as a digital currency (e.g., cryptocurrency). According to some embodiments, systems and methods can be executed to transfer cash or “hard” currency responsive to exchange of cryptocurrency supported by blockchain technology. In further example, the systems and methods are tailored to operate within a specified/defined community that ensures the efficient operation of the system by ensuring liquidity of the transfer. According to one embodiment, the system is configured to distribute stable coin, issuing the coin at a discounted value (e.g., relative to a redemption or cash equivalent face value). For example, by issuing coin at a discount the system automatically facilitates peer-to-peer physical cash transfers.

Arrangements for controlling access to a protected entity include receiving a redirected client request to access the protected entity that includes a public key of the client; granting, in response to the received redirected request, access tokens of a first type to a client using the public key of the client; identifying a conversion transaction identifying a request to convert the first type of access tokens with access tokens of a second type, the transaction designating the protected entity; determining a conversion value for converting the first-type access tokens into second-type access tokens based on at least one access parameter; converting, using the conversion value, a first sum of the first-type access tokens into a second sum of second-type access tokens; and granting the client access to the protected entity when the sum of second-type of access tokens is received as a payment from the protected entity.

Embodiments are directed to the tracking of data in a generative adversarial network (GAN) model using a distributed ledger system, such as a blockchain. A learning platform implementing a classification model receives, from a third party, a set of data examples generated by a generator model. The set of data examples are processed by the classification model, which outputs a prediction for each data example indicating whether each data example is true or false. The distributed ledger keeps a record of data examples submitted to the learning platform, as well as of predictions determined by the classification model on the learning platform. The learning platform analyzes the records of the distributed ledger, and pairs the records corresponding to the submitted data examples and the generated predictions determined by the classification model, and determines if the predictions were correct. The classification model may then be updated based upon the prediction results.

A blockchain payment channel is effected based on a series of spending transactions exchanged between parties, in which each transaction of the series of spending transactions has a future lock time, before which it cannot be committed to the blockchain, and comprises at least two spendable transaction outputs having respective digital asset values. At computer equipment of the party, a previous transaction of the series of spending transactions is received, and a function is applied to one or more function variables contained in the previous transaction to at least partially determine the current transaction. A portion of the current transaction is cryptographically signed, the signed portion comprising the at least two spendable transaction outputs, using a private key counterpart to the public key of the party, thereby computing a transaction signature for inclusion in the transaction input of the current transaction.

Provided is an operation method of a server relaying token exchange. The operation method includes receiving, from a first computing device, first token remittance information for remittance of a first token used in a first blockchain network; receiving, from a second computing device, second token remittance information for remittance of a second token used in a second blockchain network; determining whether exchange agreement coincides between the first token and the second token, based on the first token remittance information and the second token remittance information; and transmitting the first token remittance information to the second computing device and the second token remittance information to the first computing device when the exchange agreement is determined to coincide between the first and second tokens.

A system for “tagging” funds identified on a blockchain and associating a weight value therewith. The tagging profile is developed into a propagation profile wherein weight values are inherited from the tagging profile s. Propagation profile funds may be diluted by combining with non-tagged funds, similar to how ink dilutes through water. A spending history of funds of interest is developed based on replaying the funds of interest against the global transaction history of the blockchain. It is determined whether the spending history intersects with the propagation profile, thus determining how closely the two sources of funds are economically to one another. Intersection triggers actions including alert notifications or transfer of funds on the blockchain.

Methods and systems for automatically conducting a continuous forward rate agreement in a cryptocurrency using smart contracts. An obligation object is generated and provided with control of a first smart contract, which may be a collateralized debt position smart contract, and control of a lender amount. The obligation object is executed to update balances for first and second parties until the obligation object is liquidated or terminated. Additional parties may be introduced. Upon liquidation or termination, the obligation object accounts to each of the parties based on their balances, and based on tokens generated to track positions in the obligation object.

Disclosed herein is digital object generator that builds unique digital objects based on the user specific input. The unique digital objects are part of a graphic presentation to users. The user specific input is positioned on pre-configured regions of a 3D object such as a polygon. Examples of the pre-configured regions include faces of the 3D object, orbits around the 3D object, or identifiable regions associated with the 3D object. The 3D object is rendered as a part of a social media page and enables social interactions between users. In the social media page, the 3D object rotates displaying regions/faces to page visitors. In some embodiments, the 3D object is implemented as a pet or companion of a user avatar in a virtual, augmented, or extended reality space.

A control method is executed by a first node holding a first distributed ledger in which a first blockchain is managed, and includes: obtaining, from a second node, a second blockchain managed by a second distributed ledger held by the second node, and comparing the second blockchain with the first blockchain; updating the first blockchain by adding the greater of at least one first different block contained in the first blockchain but not the second blockchain and at least one second different block contained in the second blockchain but not the first blockchain, after at least one common block, and adding at least one additional block containing at least one instance of transaction data contained in the lesser; and determining whether at least two instances of transaction data each containing at least two instances of contract information that conflict with each other are contained in the updated first blockchain.

Systems and methods for providing user-controlled access to prescribed medications are provided. A cloud-based prescription database includes prescriptions, each associated with a unique patient identifier, locations of pharmacies, and available stock for the pharmacies. A unique patient identifier is received from a user device and the related prescriptions are retrieved from the database and displayed for user selection. Pharmacies which are geographically proximate to a location of the given user device which report availability of the medication associated with the user selected prescription are displayed at a map at the given user device.