Abstract: A method and system for generating a privilege based segmented instruction prompt has been developed. Trusted instructions defining the trusted instructions as having a first privilege level, program instructions as having a second privilege level, and data instructions as having a third privilege level are received. The program instructions to implement tasks associated with the data instructions are received. The data instructions are received. The generated privilege based segmented instruction prompt includes the trusted instructions, the program instructions, and the data instructions. The privilege based segmented instruction prompt enables a generative LLM to determine whether the privilege based segmented instruction prompt is an instruction injection attack based on whether there is a conflict between the trusted instructions, the program instructions, and the data instructions in violation of the first, second, and third privilege levels.

Abstract: A non-transitory computer readable medium having computer instructions stored therein that when executed by a computer system cause the computer system to perform operations including receiving a first user input defining a dialog session comprising one or more steps of a natural language conversation flow, receiving a second user input defining a positive outcome of the dialog session, receiving, via a chat interface, a natural language input, initiating the dialog session in response to an association between the natural language input and the dialog session, receiving, via the chat interface, a subsequent natural language input, and updating a data entry associated with the custom metric in an outcome log in response the subsequent natural language input being indicative of the positive outcome of the dialog session.

Abstract: A method for reporting a success of a dialog session including generating an outcome data indicative of a positive outcome of the dialog session with at least one of the plurality of natural language responses, receiving a natural language query, converting the natural language query into a structured database query based on the metadata, performing the structured database query on a database, generating a result in response to a response data received in response to the structured database query, generating a natural language responses in response to the result and the plurality of natural language response data, sending, by the chatbot, the natural language response, generating a result metadata in response to a comparison of the result to the outcome data, and generating an outcome log in response to the result metadata wherein the outcome log includes an indication of the positive outcome of the dialog session.

Abstract: Embodiments provide a generative AI creation framework to a customized generative AI stack using a foundational model (such as GPT) based on user-defined prompts, a natural language description of the task to be accomplished, and domain adaptation. In one embodiment, organization-specific knowledge may be injected into either the prompt and/or the foundational model. In this way, the customized generative AI stack thus supports a full spectrum of domain-adaptive prompts to enable a full spectrum of personalized and adaptive AI chat applications.

Abstract: Embodiments provide a generative AI creation framework to a customized generative AI stack using a foundational model (such as GPT) based on user-defined prompts, a natural language description of the task to be accomplished, and domain adaptation. In one embodiment, organization-specific knowledge may be injected into either the prompt and/or the foundational model. In this way, the customized generative AI stack thus supports a full spectrum of domain-adaptive prompts to enable a full spectrum of personalized and adaptive AI chat applications.

Abstract: A method for reporting a success of a dialog session including generating an outcome data indicative of a positive outcome of the dialog session with at least one of the plurality of natural language responses, receiving a natural language query, converting the natural language query into a structured database query based on the metadata, performing the structured database query on a database, generating a result in response to a response data received in response to the structured database query, generating a natural language responses in response to the result and the plurality of natural language response data, sending, by the chatbot, the natural language response, generating a result metadata in response to a comparison of the result to the outcome data, and generating an outcome log in response to the result metadata wherein the outcome log includes an indication of the positive outcome of the dialog session.

Abstract: A method for generating a well completion plan includes: evaluating a plurality of different well completion plans using a reservoir simulator to calculate dynamic flows of fluid through a subsurface formation, each well completion plan having a flow control device with location and associated flow setting or rating, and optionally a packer and location to provide output data for each well completion plan evaluation; developing a surrogate reservoir model using the output data and input data for each well completion plan evaluation; using intelligent sequential sampling of the output and input data for each well completion plan evaluation to provide intelligent sequential sampling data in response to the surrogate reservoir model not meeting a validation criterion; updating the surrogate reservoir model using the intelligent sequential sampling data; and iterating the using and the updating using a latest surrogate reservoir model until the latest surrogate reservoir model meets the validation criterion.

Abstract: A method for generating a well completion plan includes: evaluating a plurality of different well completion plans using a reservoir simulator to calculate dynamic flows of fluid through a subsurface formation, each well completion plan having a flow control device with location and associated flow setting or rating, and optionally a packer and location to provide output data for each well completion plan evaluation; developing a surrogate reservoir model using the output data and input data for each well completion plan evaluation; using intelligent sequential sampling of the output and input data for each well completion plan evaluation to provide intelligent sequential sampling data in response to the surrogate reservoir model not meeting a validation criterion; updating the surrogate reservoir model using the intelligent sequential sampling data; and iterating the using and the updating using a latest surrogate reservoir model until the latest surrogate reservoir model meets the validation criterion.

Abstract: According to some embodiments, a system may include a communication port to exchange information with a client device associated with an industrial control system. A network security server coupled to the communication port may include a computer processor adapted to provide a network security service for the client device. The computer processor may further be adapted to record security information about the client device via a blockchain verification process (e.g., by registering a validation result within a distributed ledger). The network security service might comprise, for example, an integrity attestation service providing software verification for the client device.

Abstract: According to some embodiments, a system may include a communication port to exchange information with a client device associated with an industrial control system. A network security server coupled to the communication port may include a computer processor adapted to provide a network security service for the client device. The computer processor may further be adapted to record security information about the client device via a blockchain verification process (e.g., by registering a validation result within a distributed ledger). The network security service might comprise, for example, an integrity attestation service providing software verification for the client device.

Abstract: A request is received from a requestor for security credentials. An initial credential authority is selected based upon a first predetermined criteria. When the initial credentials authority is not available, a back-up credentials authority is chosen based upon a second predetermined criteria. The security credentials are obtained from the back-up certificate authority. The security credentials are transmitted to the requestor.