Abstract: Reinforcement learning enables a framework of information technology assets that include software elements, computational hardware assets, and/or, bundled software and computational hardware systems and products. The performance of successive sessions of an inner loop reinforcement learning is directed and monitored by an outer loop reinforcement learning wherein the outer loop reinforcement learning is designed to reduce financial costs and computational asset requirements and/or optimize learning time in successive instantiations of inner loop reinforcement learning training sessions. The framework enables consideration of the license costs of domain specific simulators, the usage cost of hardware platforms, and the progress of a particular reinforcement learning training. The framework further enables reductions of these costs to orchestrate and train a neural network under budget constraints with respect to the available hardware and software licenses available at runtime.

Abstract: In implementations of reviewing document designs, a document review system can import reviewer comments to a design application used to author a document design. The reviewer comments can be made by a reviewer via a review application implemented on an additional computing device other than the computing device implementing the design application. The document review system can add, via the design application, a reply comment to the reviewer comment. The reply comment can be made by a designer of the document design as part of a comment hierarchy that indicates comment sequences and comment links for the document design. The document review system can also export, to the review application, a review document representing the document design that preserves the comment hierarchy in the document design.

Abstract: Digital annotation and digital content linking techniques implemented by digital content generation system as part of a computing device are described. The system is configured to convert a digital document including an object from a first format to a second format, receiving the digital document in the second format with an annotation associated with the object, converting the digital document in the second format with the annotation associated with the object to the first format, and maintaining the association between the annotation and the object subsequent to an alteration in a page sequence of the document in the first format, or movement of the object.

Abstract: In implementations of reviewing document designs, a document review system can import reviewer comments to a design application used to author a document design. The reviewer comments can be made by a reviewer via a review application implemented on an additional computing device other than the computing device implementing the design application. The document review system can add, via the design application, a reply comment to the reviewer comment. The reply comment can be made by a designer of the document design as part of a comment hierarchy that indicates comment sequences and comment links for the document design. The document review system can also export, to the review application, a review document representing the document design that preserves the comment hierarchy in the document design.

Abstract: Digital annotation and digital content linking techniques implemented by digital content generation system as part of a computing device are described. The system is configured to convert a digital document including an object from a first format to a second format, receiving the digital document in the second format with an annotation associated with the object, converting the digital document in the second format with the annotation associated with the object to the first format, and maintaining the association between the annotation and the object subsequent to an alteration in a page sequence of the document in the first format, or movement of the object.

Abstract: Reinforcement learning enables a framework of information technology assets that include software elements, computational hardware assets, and/or, bundled software and computational hardware systems and products. The performance of successive sessions of an inner loop reinforcement learning is directed and monitored by an outer loop reinforcement learning wherein the outer loop reinforcement learning is designed to reduce financial costs and computational asset requirements and/or optimize learning time in successive instantiations of inner loop reinforcement learning training sessions. The framework enables consideration of the license costs of domain specific simulators, the usage cost of hardware platforms, and the progress of a particular reinforcement learning training. The framework further enables reductions of these costs to orchestrate and train a neural network under budget constraints with respect to the available hardware and software licenses available at runtime.