Abstract: A data analysis and processing method includes forming an initial assembly of datasets comprising multiple entities, where each entity is a collection of variables and relationships that define how entities interact with each other, simulating an evolution of the initial assembly by performing multiple iterations in which a first iteration uses the initial assembly as a starting assembly, and querying, during the simulating, the evolution of the initial assembly, for datasets that meet an optimality criterion.

Abstract: A data analysis and processing method includes forming an initial assembly of datasets comprising multiple entities, where each entity is a collection of variables and relationships that define how entities interact with each other, simulating an evolution of the initial assembly by performing multiple iterations in which a first iteration uses the initial assembly as a starting assembly, and querying, during the simulating, the evolution of the initial assembly, for datasets that meet an optimality criterion.

Abstract: Optimization of existing neural networks and optimization of newly defined neural networks is provided. The system starts from an existing neural network with a known state or from a set of desired characteristics for a newly defined neural network and creates a first generation of candidate neural networks with random variations of architectural structures and hyperparameters. Fitness functions are established to evaluate the candidate neural networks. Each candidate neural network is trained and operated and then evaluated using the fitness functions. Top performing architectural structures and hyperparameters are identified and used to create a second generation of candidate neural networks that trained, operated and evaluated. The process iteratively continues until an optimized candidate neural network is determined.

Abstract: A data analysis and processing method includes forming an initial assembly of datasets comprising multiple entities, where each entity is a collection of variables and relationships that define how entities interact with each other, simulating an evolution of the initial assembly by performing multiple iterations in which a first iteration uses the initial assembly as a starting assembly, and querying, during the simulating, the evolution of the initial assembly, for datasets that meet an optimality criterion.

Abstract: A collapsible member that includes a base. The base includes slots that are formed therein. A projection member extends from the base and includes at least two stepped portions that are spaced from each other. The at least two stepped portions include a varying thickness allowing a controlled collapse of the collapsible member in response to application of a predetermined force.