Cornell Chronicle: Study uses neural networks to define Dada. “To make a Dadaist poem, artist Tristan Tzara once said, cut out each word of a newspaper article. Put the words into a bag and shake. Remove the words from the bag one at a time, and write them down in that order. This ‘bag of words’ method is not entirely different from how artificial intelligence algorithms identify words and images, breaking them down into components one step at a time. The similarity inspired Cornell researchers to explore whether an algorithm could be trained to differentiate digitized Dadaist journals from non-Dada avant-garde journals – a formidable task, given that many consider Dada inherently undefinable.”
Cornell University: Freedom on the Move launches database of fugitives from American slavery. “Freedom on the Move (FOTM), an online project devoted to fugitives from slavery in North America, is enlisting the help of the public to create a database for tens of thousands of advertisements placed by enslavers who wanted to recapture self-liberating Africans and African-Americans…. The free, open-source site has been designed to be accessible to the public. Users can quickly set up an account and begin working with digitized versions of the advertisements. Users transcribe the text of an advertisement and then answer questions about the ad and the person it describes. They can choose to transcribe ads from a particular state or specific time period, depending on their areas of interest.” I’m sure you’ve heard of this project before – it looks like I mentioned it in RB back in 2016 – but now it has officially launched.
Cornell University: New maps light up information on birds. “Move over, range maps. A new series of dynamic bird maps from the Cornell Lab of Ornithology reveals unprecedented details not only about where the birds are, but how their numbers and habitats change through the seasons and years. Unlocking this wealth of information required more than 114 years of cloud computing time to process observations recorded in eBird by more than 120,000 bird watchers across North America, along with satellite imagery from NASA.”
Cornell Chronicle: AI project could lead to reliable forecasting – of fashion. “Doctoral students Mengyun Shi and Menglin Jia from Human Ecology’s Department of Fiber Science & Apparel Design, will draw on images and metadata from the Bloomsbury Fashion Photography Archive to explore smart and rapid archiving and classification of fashion images through the application of machine learning and artificial intelligence.”
Cornell Daily Sun: Athletics Department Launches Crowdfunding Campaign for Digital Library . “Over 125 years of Cornell athletics history sits on the shelves of Associate Director of Athletics for Communications Jeremy Hartigan’s office in Schoellkopf House. These shelves house a catalogue of every varsity athlete who has lettered at Cornell, football scrapbooks dating back to 1887 that include game tickets and newspaper clippings and meeting minutes from the earliest University Athletic Council. In order to preserve these records that have been stored away for decades, the Athletics Communications team has begun a crowdfunding campaign to create a digital library.”
Imperial & Global Forum: Amazing new digital archive of political maps for imperial and global historians. “In case you missed it (I was tweeting about it A LOT last week), Cornell Library’s Digital Collections have just made available an amazing archive – the PJ Mode Collection – consisting of around 800 political maps that should be on the radar of anyone working on imperial and global history. They. Are. Awesome.”
Nieman Lab: How The Wall Street Journal is preparing its journalists to detect deepfakes. “We at The Wall Street Journal are taking this threat seriously and have launched an internal deepfakes task force led by the Ethics & Standards and the Research & Development teams. This group, the WSJ Media Forensics Committee, is comprised of video, photo, visuals, research, platform, and news editors who have been trained in deepfake detection. Beyond this core effort, we’re hosting training seminars with reporters, developing newsroom guides, and collaborating with academic institutions such as Cornell Tech to identify ways technology can be used to combat this problem.”