Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing neural architecture search for machine learning models. In one aspect, a method comprises receiving training data for a machine learning, generating a plurality of candidate neural networks for performing the machine learning task, wherein each candidate neural network comprises a plurality of instances of a layer block composed of a plurality of layers, for each candidate neural network, selecting a respective type for each of the plurality of layers from a set of layer types that comprises, training the candidate neural network and evaluating performance scores for the trained candidate neural networks as applied to the machine learning task, and determining a final neural network for performing the machine learning task based at least on the performance scores for the candidate neural networks.

Abstract: A wall block, system, and method for creating a straight and/or curved wall such that the front and back sides of the wall will have generally the same appearance. The block is asymmetrical and is designed to abut the ends of like blocks that are upright or inverted relative thereto.

Abstract: A wall block, system, and method for creating a straight and/or curved wall such that the front and back sides of the wall will have generally the same appearance. The block is asymmetrical and is designed to abut the ends of like blocks that are upright or inverted relative thereto.

Abstract: A masonry block that may be used in construction of block walls particularly retaining walls for retaining soil and preventing soil erosion. A masonry block having at least one body with a front face, back face, a pair of sides extending therebetween a top face and a bottom face, defining a block having six major surfaces.