You wouldn’t use an academic search engine to look for cat videos — but if there’s a video with cats in it that goes with an academic paper, the latest version of Semantic Scholar just might find it for you.
Semantic Scholar is the AI-based search engine that’s been developed by the Seattle-based Allen Institute for Artificial Intelligence, or AI2, specifically to sift through research for the most relevant results.
Over the past three years, the project has indexed more than 40 million research papers. Now AI2’s researchers have turned their algorithms loose to link those papers to associated presentation slides, Github code libraries, summaries of clinical trials, news articles, blogs, social-media postings and videos.
That includes a video with pictures of cats and dogs in it, tied to a paper titled “Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks.”
