An XR Environment for AI Education: Design and First Implementation
Yiyin Gu, Miguel A. Feijoo‐Garcia, Yiqun Zhang, Alejandra J. Magana, Bedřich Beneš, Voicu S. Popescu · 2024
This work in progress paper presents and motivates the design of a novel extended reality (XR) environment for artificial intelligence (AI) education, and presents its first implementation. The learner is seated at a table and wears an XR headset that allows them to see both the real world and a visualization of a neural network. The visualization is adjustable. The learner can inspect each layer, each neuron, and each connection. The learner can also choose a different input image, or create their own image to feed to the network. The inference is computed on the headset, in real time. The neural network configuration and its weights are loaded from an onnx file, which supports a variety of architectures as well as changing the weights to illustrate the training process.