Scientists around the world are gearing up to study the first images taken by the James Webb Space Telescope, which are to be released on July 12.
Some astronomers will be running machine-learning algorithms on the data to detect and classify galaxies in deep space at a level of detail never seen before. Brant Robertson, an astrophysics professor at the University of California, Santa Cruz, in the US believes the telescope's snaps will lead to breakthroughs that will help us better understand how the universe formed some 13.7 billion years ago.
"The JWST data is exciting because it gives us an unprecedented window on the infrared universe, with a resolution that we've only dreamed about until now," he told The Register. Robertson helped develop Morpheus, a machine-learning model trained to pore over pixels and pick out blurry blob-shaped objects from the deep abyss of space and determine whether these structures are galaxies or not, and if so, of what type.