Abstract: A method and apparatus of a device of determining a reduced space neural network architecture is described. In an exemplary embodiment, the device receives a full space neural network architecture, wherein the full space architecture includes a first plurality of nodes and a set of weights. The device may further transform the set of weights. In addition, the device may also reduce the first plurality of nodes using the transformed set of weights to create second plurality of nodes. Furthermore, the device can create the reduced space neural network architecture using the second plurality of nodes.

Abstract: A method for the computerized design of real-world object uses knowledge of already existing designs and their physical performance numbers. During the design process, a plurality of design variables are adapted, and the result of the design has improved physical performance numbers when converted into the real-world Object. The design process is decomposed in parallel streams of optimization modules, with each optimization module individually optimizing a group of interrelated design variables. The functional interrelation between design variables is evaluated using an interaction information representing the functional dependency between the design variables and the physical performance numbers.