Collaborating Authors

Giant squid's genome is sequenced for the first time

Daily Mail - Science & tech

Scientists have published the full genome sequence of the mysterious giant squid, which seems to hint at the creature's high intelligence. An international research team found that their genes look a lot like other animals – with a genome size not far behind that of humans. The mysterious squid, Architeuthius dux, has eyes as big as dinner plates and tentacles that snatch prey from 10 yards away. Its average length is around 33 feet – approximately the size of an average-sized school bus. But these legendary creatures are notoriously elusive and sightings are rare, making them difficult to study.

Scientists unlock secrets about mysterious giant squid

FOX News

Fox News Flash top headlines for Jan. 17 are here. Check out what's clicking on Not much is known about the mysterious giant squid, a creature that was first captured on film in 2005. Now, researchers have decoded the giant cephalopod's genome, hoping to unlock more secrets about the legendary squid. The research, published in Giga Science, notes the giant squid has an enormous genome, with an estimated 2.7 billion DNA base pairs.

How Deep Learning Deciphers Historial Documents NVIDIA Blog


Deep learning researchers are hitting the books. By building AI tools to transcribe historical texts in antiquated scripts letter by letter, they're creating an invaluable resource for researchers who study centuries-old documents. Many old documents have been digitized as scans or photographs of physical pages. But while obsolete scripts like Greek miniscule or German Fraktur may be readable by experts, the text on these scanned pages is neither legible to a broad audience nor searchable by computers. Hiring transcribers to turn manuscripts into typed text is a lengthy and expensive process.

How AI helps historians solve ancient puzzles


Uncovering evidence for historical theories and identifying patterns in past events has long been hindered by the labour-intensive process of inputting data from artefacts and handwritten records. The adoption of artificial intelligence and machine learning techniques is speeding up such research and drawing attention to overlooked information. But this approach, known as "digital humanities", is in a battle for funding against more future-focused applications of AI. "There is a lot of interest in digital humanities, but there is not a lot of money," says Ilan Shimshoni, professor of computer vision and machine learning at the University of Haifa in Israel, where he works on archaeological projects that include reassembling artefacts from photos of fragments. "If you want to do an analysis of Facebook you'll get much more money than if you want to look at ancient Greek artefacts." Archaeological puzzles may not seem as urgent as computer science projects in healthcare, finance and other industries, but applying algorithmic techniques to historical research can improve AI's capabilities, says Ayellet Tal, an archaeological and computer science researcher at Israel's Technion University.

Machine learning and big data are unlocking Europe's archives


From wars to weddings, Europe's history is stored in billions of archival pages across the continent. While many archives try to make their documents public, finding information in them remains a low-tech affair. Simple page scans do not offer the metadata such as dates, names, locations that often interest researchers. Copying this information for later use is also time-consuming. These issues are well-known in Amsterdam, which is trying to disclose its entire archives.