Abstract: Generative AI systems and methods are developed to provide recommendations regarding the control, optimization, and troubleshooting of industrial equipment and manufacturing systems as determined from a range of available data sources. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode. Users and/or AI agents (i.e., a form of “agentic AI”) may then subscribe to such information for the use in connection with their own manufacturing systems.

Abstract: Generative AI systems and methods are provided to produce leading indicators of economic activity based on, for example, agricultural, fishing, mining, lumber harvesting, environmental, or ecological attributes and other factors determined from a range of available data sources. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode. Users may then subscribe to the date for the use in economic forecasting.

Abstract: Generative AI systems and methods are developed to provide recommendations regarding the prevention, detection, mitigation, and/or remediation of cybersecurity threats as determined from a range of available data sources. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode. Users and/or AI agents (i.e., a form of “agentic AI”) may then subscribe to the data for the use in cybersecurity analytics, protection, mitigation, containment, remediation, and/or counterattacks of cybersecurity threats.

Abstract: Generative AI systems and methods are provided to provide recommendations as to whether a particular security associated with a corporate entity and/or its competitors should be purchased, sold, or held, as determined from a range of available data sources. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode. Users may then subscribe to the date for the use in economic forecasting.

Abstract: Generative AI systems and methods are provided to provide recommendations as to whether a particular security associated with a corporate entity and/or its competitors should be purchased, sold, or held, as determined from a range of available data sources. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode. Users may then subscribe to the date for the use in economic forecasting.

Abstract: Generative AI systems and methods are developed to provide recommendations regarding product sales, pricing, inventory, orders, manufacturing, distribution, shipping, packaging or other product analytics as determined from a range of available data sources. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode. Users and/or AI agents (i.e., a form “agentic AI”) may then subscribe to the date for the use in economic forecasting.

Abstract: Generative AI systems and methods are provided to produce leading indicators of economic activity based on, for example, agricultural, fishing, mining, lumber harvesting, environmental, or ecological attributes and other factors determined from a range of available data sources. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode. Users may then subscribe to the date for the use in economic forecasting.

Abstract: Predictive analytics techniques are provided to produce leading indicators of economic activity based on agricultural, fishing, mining, lumber harvesting, environmental, or ecological attributes and other factors determined from a range of available data sources. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to manage process excursions. An example apparatus includes a digital twin comparer to determine when a product fails to satisfy a tolerance metric of a digital twin, and a fingerprint manager to generate a fingerprint corresponding to a sensor pattern. The example apparatus also includes a node interfacer to determine a number of workstations of a process control system that exhibit the fingerprint, and an excursion statistics calculator to invoke a corrective action for respective ones of the number of workstations, the corrective action based on a threshold count of the number of workstations that exhibit the fingerprint.

Abstract: Predictive analytics techniques are used to produce leading indicators of economic activity based on factors determined from a range of available data sources, such as public and/or private transportation data. A fee-based subscription system may be provided for the sharing of leading indicators to users. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode.

Abstract: Predictive analytics techniques are used to produce leading indicators of economic activity based on factors determined from a range of available data sources, such as public and/or private transportation data. A fee-based subscription system may be provided for the sharing of leading indicators to users. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode.

Abstract: Predictive analytics techniques are used to produce leading indicators of economic activity based on factors determined from a range of available data sources, such as public and/or private transportation data. A fee-based subscription system may be provided for the sharing of leading indicators to users. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode.

Abstract: Orchestration and/or management of services on deployed computing, electronic, appliance and like devices are described. A service orchestration and/or management system (“SOMS”) may be configured to provide for orchestration and/or management of services to one or more deployed devices. The SOMS may obtain information from deployed devices, such as status, capabilities and service metadata. The SOMS may then encapsulate and store the obtained information for later use. The SOMS may also store service information, facilitate creation of services based on stored service definition meta-data, modeling or simulating a service prior to deployment, and deployment of a service to remotely deployed devices followed by activation to begin operation of the service. Other embodiments may be described and claimed.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to manage process excursions. An example apparatus includes a digital twin comparer to determine when a product fails to satisfy a tolerance metric of a digital twin, and a fingerprint manager to generate a fingerprint corresponding to a sensor pattern. The example apparatus also includes a node interfacer to determine a number of workstations of a process control system that exhibit the fingerprint, and an excursion statistics calculator to invoke a corrective action for respective ones of the number of workstations, the corrective action based on a threshold count of the number of workstations that exhibit the fingerprint.

Abstract: Orchestration and/or management of services on deployed computing, electronic, appliance and like devices are described. A service orchestration and/or management system (“SOMS”) may be configured to provide for orchestration and/or management of services to one or more deployed devices. The SOMS may obtain information from deployed devices, such as status, capabilities and service metadata. The SOMS may then encapsulate and store the obtained information for later use. The SOMS may also store service information, facilitate creation of services based on stored service definition meta-data, modeling or simulating a service prior to deployment, and deployment of a service to remotely deployed devices followed by activation to begin operation of the service. Other embodiments may be described and claimed.