Abstract: The present disclosure relates generally to storing computer models, and more specifically to a platform for achieving replicability of a computer model (e.g., a trained machine-learning algorithm) by storing and providing access to data associated with the computer model using an immutable and decentralized ledger system (e.g., a blockchain ledger) and a distributed database. An exemplary computer-enabled method for storing a computer model, the method comprises: receiving data associated with the computer model; generating one or more asset files based on the data associated with the computer model; generating one or more hash values corresponding to the one or more asset files; generating one or more of location trackers corresponding to the one or more asset files; generating a ledger entry comprising the one or more hash values and the one or more location trackers; and adding the ledger entry to a blockchain ledger.

Abstract: Systems and methods for secure and accountable execution of computer scripts are disclosed. A system for validating an execution of a set of computer instructions may be configured to receive a first cryptographic hash, the first cryptographic hash corresponding to the set of computer instructions, to receive a second cryptographic hash, the second cryptographic hash corresponding to a runtime utility, wherein the runtime utility is configured to execute the set of computer instructions, to generate a ledger entry comprising the first cryptographic hash, the second cryptographic hash, and an indicator of success, and to add the ledger entry to a blockchain ledger, wherein the blockchain ledger is configured to receive the ledger entry from an authenticated node.

Abstract: The present disclosure relates generally to storing computer models, and more specifically to a platform for achieving replicability of a computer model (e.g., a trained machine-learning algorithm) by storing and providing access to data associated with the computer model using an immutable and decentralized ledger system (e.g., a blockchain ledger) and a distributed database. An exemplary computer-enabled method for storing a computer model, the method comprises: receiving data associated with the computer model; generating one or more asset files based on the data associated with the computer model; generating one or more hash values corresponding to the one or more asset files; generating one or more of location trackers corresponding to the one or more asset files; generating a ledger entry comprising the one or more hash values and the one or more location trackers; and adding the ledger entry to a blockchain ledger.

Abstract: Systems and methods for implementing an automation platform that is configured to analyze computing activities from a plurality of users so as to identify potential automation processes is provided. In one or more examples, a plurality of data collection agents are deployed across a plurality of computing devices and can be configured to collect and record activities performed on the computing device by one or more users of the computing devices. In one or more examples, each agent deployed on a computing device can be configured to transmit the collected data to a central server that can store the collected data in memory. The central server can be configured to collect the data from each agent and can be configured to apply one or more data science algorithms that can be configured to cluster various activities collected by the agents into groups for potential automation.

Abstract: Systems and methods for secure and accountable execution of computer scripts are disclosed. A system for validating an execution of a set of computer instructions may be configured to receive a first cryptographic hash, the first cryptographic hash corresponding to the set of computer instructions, to receive a second cryptographic hash, the second cryptographic hash corresponding to a runtime utility, wherein the runtime utility is configured to execute the set of computer instructions, to generate a ledger entry comprising the first cryptographic hash, the second cryptographic hash, and an indicator of success, and to add the ledger entry to a blockchain ledger, wherein the blockchain ledger is configured to receive the ledger entry from an authenticated node.

Abstract: The present disclosure relates generally to storing computer models, and more specifically to a platform for achieving replicability of a computer model (e.g., a trained machine-learning algorithm) by storing and providing access to data associated with the computer model using an immutable and decentralized ledger system (e.g., a blockchain ledger) and a distributed database. An exemplary computer-enabled method for storing a computer model, the method comprises: receiving data associated with the computer model; generating one or more asset files based on the data associated with the computer model; generating one or more hash values corresponding to the one or more asset files; generating one or more of location trackers corresponding to the one or more asset files; generating a ledger entry comprising the one or more hash values and the one or more location trackers; and adding the ledger entry to a blockchain ledger.