Stanford University researchers created an inverse design codebase called SPINS that can help researchers explore different design methodologies to find fabricable optical and nanophotonic structures. [32] Vacuum fluctuations just a few nanometres from the surface of a material can cause a passing beam of relativistic electrons to emit X-rays and other high-frequency electromagnetic radiation-according to calculations done by scientists in the US, Israel and Singapore. [31] A simple, passive photonic structure made only of glass and air bubbles could perform artificial neural computing for applications in areas like facial recognition. [30] Most artificial intelligence (AI) systems try to replicate biological mechanisms and behaviors observed in nature. [29] "We basically combined advances in neural networks and machine-learning with quantum Monte Carlo tools," says Savona, referring to a large toolkit of computational methods that physicists use to study complex quantum systems. [28] As cosmologists and astrophysicists delve deeper into the darkest recesses of the universe, their need for increasingly powerful observational and computational tools has expanded exponentially. [27] Now, a team of scientists at MIT and elsewhere has developed a neural network, a form of artificial intelligence (AI), that can do much the same thing, at least to a limited extent: It can read scientific papersand render a plain-English summary in a sentence or two. [26] To address this gap in the existing literature, a team of researchers at SRI International has created a human-AI image guessing game inspired by the popular game 20 Questions (20Q), which can be used to evaluate the helpfulness of machine explanations. [25]