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Despite AI's progress in building complex software, the ubiquitous PDF remains something of a grand challenge -- a format Adobe developed in the early 1990s to preserve the precise visual appearance of documents. PDFs consist of character codes, coordinates, and rendering instructions rather than logically ordered text, and even state-of-the-art models asked to extract information from them will summarize instead, confuse footnotes with body text, or outright hallucinate contents, The Verge writes. Companies like Reducto are now tackling the problem by segmenting pages into components -- headers, tables, charts -- before routing each to specialized parsing models, an approach borrowed from computer vision techniques used in self-driving vehicles. Researchers at Hugging Face recently found roughly 1.3 billion PDFs sitting in Common Crawl alone, and the Allen Institute for AI has noted that PDFs could provide trillions of novel, high-quality training tokens from government reports, tex

The first fiber-optic cable ever laid across an ocean -- TAT-8, a nearly 6,000-kilometer line between the United States, United Kingdom, and France that carried its first traffic on December 14, 1988 -- is now being pulled off the Atlantic seabed after more than two decades of sitting dormant, bound for recycling in South Africa. Subsea Environmental Services, one of only three companies in the world whose entire business is cable recovery and recycling, began the operation last year using its new diesel-electric vessel, the MV Maasvliet, and had already brought 1,012 kilometers of the cable to the Portuguese port of Leixoes by August. TAT-8, short for Trans-Atlantic Telephone 8, was built by AT&T, British Telecom, and France Telecom, and hit full capacity within just 18 months of going live. A fault too expensive to repair took it out of service in 2002. The recovered cable is being shipped to Mertech Marine in South Africa, where it will be broken down into steel, copper, and

Climate scientists trying to predict how much hotter the planet will get have long grappled with a surprisingly stubborn problem -- clouds, which both reflect sunlight and trap heat, account for more than half the variation between climate predictions and are the main reason warming projections for the next 50 years range from 2 to 6 degrees Celsius. Two research groups are now racing to close that gap using AI, though they disagree sharply on method. Tapio Schneider at Caltech built CLIMA, a model that uses machine learning to optimize cloud parameters within traditional physics equations; it will be unveiled at a conference in Japan in March. Chris Bretherton at the Allen Institute for AI took a different path -- his ACE2 neural network, released in 2024, learns from 50 years of atmospheric data and largely bypasses physics equations altogether. Read more of this story at Slashdot.