Abstract: An example operation may include one or more of receiving an example in a blockchain network, distributing the example to a plurality of endorsing peers of the blockchain network, performing, by one or more of the endorsing peers, automated analysis of the example to determine an inference for the example, determining if there is a consensus of inference amongst the plurality of endorsing peers, and committing the example to a blockchain of the blockchain network when there is a consensus of inference.

Abstract: Authenticity of Artificial Intelligence (AI) results may be verified by creating, for an AI system, from a plurality of original inputs to form a plurality of original inference results, a plurality of original signatures of representative elements of an internal state of the AI system constructed from each individual original inference result of the plurality of original inference results. During deployment of the AI system, a matching of a plurality of deployment time inference results with a plurality of deployment time signatures, to the plurality of original signatures and the plurality of original inference results, may be verified.

Abstract: Aspects of the invention include receiving data that includes a group of n symbols to be written to a plurality of storage units. The group of symbols is mapped into a codeword of n+k symbols, each assigned to one of the storage units. The codeword is configured to allow at least one of the n symbols to be reconstructed using a subset of the n+k symbols. At least one of the n+k symbols is assigned to one of the storage units based at least in part on content of the at least one of the n+k symbols. Writing each of the n+k symbols to its assigned storage unit in the plurality of storage units is initiated. The writing includes optimizing storage capacity of the assigned storage unit based at least in part on determining that the symbol has the same content as another symbol previously stored in the storage unit.

Abstract: An example operation may include one or more of receiving an example in a blockchain network, distributing the example to a plurality of endorsing peers of the blockchain network, performing, by one or more of the endorsing peers, automated analysis of the example to determine an inference for the example, determining if there is a consensus of inference amongst the plurality of endorsing peers, and committing the example to a blockchain of the blockchain network when there is a consensus of inference.

Abstract: Authenticity of Artificial Intelligence (AI) results may be verified by creating, for an AI system, from a plurality of original inputs to form a plurality of original inference results, a plurality of original signatures of representative elements of an internal state of the AI system constructed from each individual original inference result of the plurality of original inference results. During deployment of the AI system, a matching of a plurality of deployment time inference results with a plurality of deployment time signatures, to the plurality of original signatures and the plurality of original inference results, may be verified.

Abstract: An apparatus comprising a memory and a processor coupled to the memory. The processor receives input from a user, processes a first portion of the input via more than one service module while receiving a second portion of the input to determine a first speculative result, wherein processing the first portion of the input comprises executing at least one service module coupled to a corresponding speculation buffer, processes a second portion of the input via the more than one service module to determine a second speculative result, wherein processing the second portion of the input comprises executing the at least one service module coupled to the corresponding speculation buffer, processes the input via the more than one service module to determine a final output, wherein processing the input comprises executing the at least one service module coupled to the corresponding speculation buffer, and outputs the final output to the user.

Abstract: Aspects of the invention include receiving data that includes a group of n symbols to be written to a plurality of storage units. The group of symbols is mapped into a codeword of n+k symbols, each assigned to one of the storage units. The codeword is configured to allow at least one of the n symbols to be reconstructed using a subset of the n+k symbols. At least one of the n+k symbols is assigned to one of the storage units based at least in part on content of the at least one of the n+k symbols. Writing each of the n+k symbols to its assigned storage unit in the plurality of storage units is initiated. The writing includes optimizing storage capacity of the assigned storage unit based at least in part on determining that the symbol has the same content as another symbol previously stored in the storage unit.