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Understanding the inner workings of Artificial Intelligence (AI) recommendation systems may benefit children in becoming more sensible consumers of the ever-growing information in their daily lives. It may further enable deeper reflections on related ethical issues such as the filter bubble. With limited prior knowledge in math and computing, children often find AI concepts overly abstract. Inspired by optical computation, we propose a novel tangible interface, OptiDot. Through exploratory manipulation with light beams, OptiDot supports children in learning the dot product—a building block for numerous AI algorithms—and AI recommendations through embodied learning experiences. Findings of a preliminary user study with ten middle school students indicate the effectiveness of the key embodied metaphors. We also discuss the design implications and challenges of developing optical-inspired learning tools for children. 

The creation of new see-through near-eye displays (NEDs) architectures is a topic of intense research focus. A fundamental problem that each design must address is the field of view (FOV) and eyebox of NEDs are limited by etendue conservation for a fixed display optics size. Waveguide architecture provides the solution to increasing the eyebox in NEDs without increasing the optics size through exit pupil expansion. Brightness and uniformity are two key features of waveguide architecture. In this work, we focus on the brightness of the waveguide since the image uniformity can be compensated by the display engine. We show that the geometry of the waveguide sets a fundamental limit on the in-coupling efficiency for a given FOV. This limit can be used as a tool for waveguide designers to benchmark the in-coupling efficiency of their incoupler gratings. With this derived limit, we designed and optimized a metasurface-based grating (metagrating) and a surface relief grating (SRG) as in-couplers. The diffractive efficiencies of the two types of in-couplers were then compared to the theoretical efficiency limit. The metagrating's 28% efficiency surpasses the SRG's 20% efficiency and nearly matches the geometry-based limit of 29% due to the superior angular response control of metasurfaces compared to SRGs. This work provides a new understanding of the brightness efficiency limit of waveguide-based combiners and paves a novel path toward implementing metasurfaces in efficient waveguide AR displays. 

Recently, augmented reality (AR) displays have attracted considerable attention due to the highly immersive and realistic viewer experience they can provide. One key challenge of AR displays is the fundamental trade-off between the extent of the field-of-view (FOV) and the size of the eyebox, set by the conservation of etendue sets this trade-off. Exit-pupil expansion (EPE) is one possible solution to this problem. However, it comes at the cost of distributing light over a larger area, decreasing the overall system's brightness. In this work, we show that the geometry of the waveguide and the in-coupler sets a fundamental limit on how efficient the combiner can be for a given FOV. This limit can be used as a tool for waveguide designers to benchmark the in-coupling efficiency of their in-coupler gratings. We design a metasurface-based grating (metagrating) and a commonly used SRG as in-couplers using the derived limit to guide optimization. We then compare the diffractive efficiencies of the two types of in-couplers to the theoretical efficiency limit. For our chosen waveguide geometry, the metagrating's 28% efficiency surpasses the SRG's 20% efficiency and nearly matches the geometry-based limit of 29% due to the superior angular response control of metasurfaces compared to SRGs. This work provides new insight into the efficiency limit of waveguide-based combiners and paves a novel path toward implementing metasurfaces in efficient waveguide AR displays.