Neural Probabilistic Learner and Sampler (NPLS) is an algorithm that has simulated children’s non-symbolic probability learning from visual stimuli such as collections of different colors of marbles. Although NPLS closely simulates the cognitive process of probability learning, the training of such learning algorithms often uses binary encoding of inputs that represent the perceived visual stimuli, avoiding simulation of the visual perception of the stimuli. Here, the computer vision technique You Only Look Once (YOLO) (Jocher et al., 2021; Redmon et al., 2016), is integrated into the workflow of an NPLS simulation probability learning experiments with children. YOLO is a convolutional neural network (CNN) designed to detect objects. The model’s performance on marble datasets is tested through an analysis of precision and recall. Results indicate that the YOLO model, when trained sufficiently, outputs predictions on marble image datasets with high accuracy and precision. We also analyze YOLO’s suitability as a biologically plausible model of visual processing, interfering with YOLO’s training process by shortening the training time to examine the effects of perceptual errors on simulated probabilistic reasoning.

Nanoscale metamaterials exhibit extraordinary optical properties and are proposed for various technological applications. Here, a new class of novel nanoscale two-phase hybrid metamaterials is achieved by combining two major classes of traditional plasmonic materials, metals (e.g., Au) and transition metal nitrides (e.g., TaN, TiN, and ZrN) in an epitaxial thin film form via the vertically aligned nanocomposite platform. By properly controlling the nucleation of the two phases, the nanoscale artificial plasmonic lattices (APLs) consisting of highly ordered hexagonal close packed Au nanopillars in a TaN matrix are demonstrated. More specifically, uniform Au nanopillars with an average diameter of 3 nm are embedded in epitaxial TaN platform and thus form highly 3D ordered APL nanoscale metamaterials. Novel optical properties include highly anisotropic reflectance, obvious nonlinear optical properties indicating inversion symmetry breaking of the hybrid material, large permittivity tuning and negative permittivity response over a broad wavelength regime, and superior mechanical strength and ductility. The study demonstrates the novelty of the new hybrid plasmonic scheme with great potentials in versatile material selection, and, tunable APL spacing and pillar dimension, all important steps toward future designable hybrid plasmonic materials.