Abstract: Various aspects of the disclosure relate to automated and continuous monitoring of batch processing jobs executing in a multi-node environment. The autocorrecting batch processing system generates prompts based on the identified failure information. When the autocorrecting batch processing system identifies a failure event a quantum artificial intelligence (AI) prompt generator generates a prompt for use when automatically generating code snippets. The prompt is stored in a non-linear database and is passed to a generative AI engine, which is trained to generate multiple code snippets based on the prompts generated by a quantum AI prompt generator. These code snippets are automatically evaluated against smart contracts stored in an enterprise organization's blockchain network to ensure that AI generated code snippets adhere to the organization's security regulations. Approved code segments are provided to the faulted node for inclusion in real-time to resume the batch processing job from the point of failure.

Abstract: Various aspects of the disclosure relate to automated and continuous monitoring of batch processing jobs executing in a multi-node environment. The autocorrecting batch processing system generates prompts based on the identified failure information. When the autocorrecting batch processing system identifies a failure event a quantum artificial intelligence (AI) prompt generator generates a prompt for use when automatically generating code snippets. The prompt is stored in a non-linear database and is passed to a generative AI engine, which is trained to generate multiple code snippets based on the prompts generated by a quantum AI prompt generator. These code snippets are automatically evaluated against smart contracts stored in an enterprise organization's blockchain network to ensure that AI generated code snippets adhere to the organization's security regulations. Approved code segments are provided to the faulted node for inclusion in real-time to resume the batch processing job from the point of failure.

Abstract: Various aspects of the disclosure relate to automated and continuous monitoring of batch processing jobs executing in a multi-node environment. The autocorrecting batch processing system generates prompts based on the identified failure information. When the autocorrecting batch processing system identifies a failure event a quantum artificial intelligence (AI) prompt generator generates a prompt for use when automatically generating code snippets. The prompt is stored in a non-linear database and is passed to a generative AI engine, which is trained to generate multiple code snippets based on the prompts generated by a quantum AI prompt generator. These code snippets are automatically evaluated against smart contracts stored in an enterprise organization's blockchain network to ensure that AI generated code snippets adhere to the organization's security regulations. Approved code segments are provided to the faulted node for inclusion in real-time to resume the batch processing job from the point of failure.