The desire to disappear has been strong throughout history. It didn't go well for the protagonist in H. G. Wells's The Invisible Man, but that is because his invisibility was permanent. What was needed – and what was longed for – was a means of disappearing temporarily, as popularised by Harry Potter's invisibility cloak. Metamaterials developed in the early 21st century gave hope that a garment offering universal invisibility was feasible. But while some forms of cloaking device did become possible, the sheer level of engineering required to produce them meant they remained rare, ultra-expensive and out of reach to the vast majority.

In machine translation, rare words continue to be a problem for the dominant encoder-decoder architecture, especially in low-resource and out-of-domain translation settings. Human translators solve this problem with monolingual or bilingual dictionaries. In this paper, we propose appending definitions from a bilingual dictionary to source sentences and using attention masking to link together rare words with their definitions. We find that including definitions for rare words improves performance by up to 1.0 BLEU and 1.6 MacroF1.

Harry Potter's Invisible Cloak will no longer be a magic artifact from a book. Researchers from the University of Maryland have developed a sweater that makes you'invisible' in front of the AI models that detect persons. In simple words, the models that detect persons (or any other object) divide an image into grid cells with equal-dimensional regions. Think of a chessboard or a Rubik's cube! Each grid cell (each square in the chessboard or each section of the Rubik's cube) will: Detect objects within them Enclose them into a bounding box, and Predict their localization, class (think of a category), and probability Then, the model will remove all bounding boxes with lower probability scores and establish the class of each object* Now back to the invisibility cloak.

Invisibility is no longer science fiction. Researchers have developed a unique light wave that, when beamed through an object, makes the object appear invisible to cameras and even the human eye. The backstory: If you think invisibility cloaks are only for wizards, think again. Scientists have been trying to solve this challenge since long before Dumbledore bestowed the hallow cloak upon Harry Potter, and invisibility tech is for real. With the tricks of the camera, scientists can capture pictures of what's behind an object, then project them onto the object's surface, making it seem to disappear.

Metamaterials are artificial materials engineered to have properties not found in naturally occurring materials, and they are best known as materials for invisibility cloaks often featured in sci-fi novels or games. By precisely designing artificial atoms smaller than the wavelength of light, and by controlling the polarization and spin of light, researchers achieve new optical properties that are not found in nature. However, the current process requires much trial and error to find the right material. Such efforts are time-consuming and inefficient; artificial intelligence (AI) could provide a solution for this problem. The research group of Prof. Junsuk Rho, Sunae So and Jungho Mun of Department of Mechanical Engineering and Department of Chemical Engineering at POSTECH have developed a design with a higher degree of freedom that allows researchers to choose materials and design photonic structures arbitrarily by using deep learning.

From Star Trek to Harry Potter, invisibility cloaks are a popular theme in science fiction. And now researchers have developed a new technique that could turn the futuristic technology into a reality. The technique involves disrupting the way that light waves pass through opaque objects, and could lead to active camouflage. While researchers are yet to demonstrate it in practice, they are confident that experiments will soon confirm the idea. The concept involves shining a laser onto a material from above to pump it full of energy.