Abstract: The present disclosure relates to techniques for developing artificial intelligence algorithms by distributing analytics to multiple sources of privacy protected, harmonized data. Particularly, aspects are directed to a computer implemented method that includes receiving an algorithm and input data requirements associated with the algorithm, identifying data assets as being available from a data host based on the input data requirements, curating the data assets within a data storage structure that is within infrastructure of the data host, and integrating the algorithm into a secure capsule computing framework. The secure capsule computing framework serves the algorithm to the data assets within the data storage structure in a secure manner that preserves privacy of the data assets and the algorithm. The computer implemented method further includes running the data assets through the algorithm to obtain an inference.

Abstract: The present disclosure relates to techniques for developing artificial intelligence algorithms by distributing analytics to multiple sources of privacy protected, harmonized data. Particularly, aspects are directed to a computer implemented method that includes receiving an algorithm and input data requirements associated with the algorithm, identifying data assets as being available from a data host based on the input data requirements, curating the data assets within a data storage structure that is within infrastructure of the data host, and integrating the algorithm into a secure capsule computing framework. The secure capsule computing framework serves the algorithm to the data assets within the data storage structure in a secure manner that preserves privacy of the data assets and the algorithm. The computer implemented method further includes running the data assets through the algorithm to obtain an inference.

Abstract: The present disclosure relates to techniques for developing artificial intelligence algorithms by distributing analytics to multiple sources of privacy protected, harmonized data. Particularly, aspects are directed to a computer implemented method that includes receiving an algorithm and input data requirements associated with the algorithm, identifying data assets as being available from a data host based on the input data requirements, curating the data assets within a data storage structure that is within infrastructure of the data host, and integrating the algorithm into a secure capsule computing framework. The secure capsule computing framework serves the algorithm to the data assets within the data storage structure in a secure manner that preserves privacy of the data assets and the algorithm. The computer implemented method further includes running the data assets through the algorithm to obtain an inference.

Abstract: The present disclosure relates to techniques for developing artificial intelligence algorithms by distributing analytics to multiple sources of privacy protected, harmonized data. Particularly, aspects are directed to a computer implemented method that includes receiving an algorithm and input data requirements associated with the algorithm, identifying data assets as being available from a data host based on the input data requirements, curating the data assets within a data storage structure that is within infrastructure of the data host, and integrating the algorithm into a secure capsule computing framework. The secure capsule computing framework serves the algorithm to the data assets within the data storage structure in a secure manner that preserves privacy of the data assets and the algorithm. The computer implemented method further includes running the data assets through the algorithm to obtain an inference.

Abstract: The present disclosure relates to techniques for developing artificial intelligence algorithms by distributing analytics to multiple sources of privacy protected, harmonized data. Particularly, aspects are directed to a computer implemented method that includes receiving an algorithm and input data requirements associated with the algorithm, identifying data assets as being available from a data host based on the input data requirements, curating the data assets within a data storage structure that is within infrastructure of the data host, and integrating the algorithm into a secure capsule computing framework. The secure capsule computing framework serves the algorithm to the data assets within the data storage structure in a secure manner that preserves privacy of the data assets and the algorithm. The computer implemented method further includes running the data assets through the algorithm to obtain an inference.

Abstract: The present disclosure relates to techniques for developing artificial intelligence algorithms by distributing analytics to multiple sources of privacy protected, harmonized data. Particularly, aspects are directed to a computer implemented method that includes receiving an algorithm and input data requirements associated with the algorithm, identifying data assets as being available from a data host based on the input data requirements, curating the data assets within a data storage structure that is within infrastructure of the data host, and integrating the algorithm into a secure capsule computing framework. The secure capsule computing framework serves the algorithm to the data assets within the data storage structure in a secure manner that preserves privacy of the data assets and the algorithm. The computer implemented method further includes running the data assets through the algorithm to obtain an inference.

Abstract: According to one embodiment, a method of initiating and/or routing communications within a system comprised of a plurality of disparate sub-systems is provided. The method includes collecting information from one or more sub-systems regarding participants in the integrated system, wherein collected information includes one or more of schedule, status, and contact information, wherein the collected information is stored in a central directory. A communication initiated by one of the sub-systems is received, and an event is identified within the received communication. A workflow plan is initiated based on the identified event, wherein the workflow plan utilizes collected information to generate workflow-driven communications to one or more participants. The workflow-driven communications is then delivered to the one or more participants.

Abstract: A borehole network including first and second end surface locations and at least one intermediate surface location interconnected by a subterranean path, and a method for connecting a subterranean path between a first borehole including a directional section and a second borehole including a directional section. A directional drilling component is drilled in at least one of the directional sections to obtain a required proximity between the first and second boreholes. An intersecting component is drilled, utilizing magnetic ranging techniques, from one directional section to provide a borehole intersection between the first and second boreholes, thereby connecting the subterranean path.

Abstract: A panel carrying device for holding a concrete form panel is disclosed. The device comprises an elongate handle with opposite ends. A pair of elongate arms are each mounted on one of the opposite ends of the handle with the handle extending between the arms. Each of the arms has a first end and a second end, with the first end of each of the arms being insertable into a hole in the concrete form panel. An elongate slot is formed in each of the arms for engaging an edge of the wall of the panel about the hole in the panel. The slot is formed in the first end of the arm. A longitudinal axis of the slot of each of the arms is positioned substantially perpendicular to a longitudinal axis of the respective arm for aligning the wall of the panel substantially parallel to the handle when each of the arms is extended through the holes in the wall of the concrete form panel.