There is now a backlog of 50 million published research papers dating back to 1665. Researchers, scientists, and academics around the world each year publish almost 2.5 million scientific papers, and the rate of publishing papers each day keeps on rising. So it’s impossible to read all the published papers and it is also a very daunting task to find a specific paper.
Microsoft co-founder and leader of the nonprofit Allen Institute for Artificial Intelligence Paul Allen came up with a plan. Semantic Scholar, The Allen Institute’s latest effort is a search engine for scientific-paper fueled by machine learning and other artificial intelligence systems.
The search engine which is focused on computer science papers Semantic Scholar went online in November 2015. Today it had an expansion, from now the engine also added neuroscience related scientific papers which replenish its database with more than 10 million papers. Semantic Scholar is showcased as a sophisticated alternative to Google Scholar and it uses natural language processing algorithms and AI systems to find the specific paper anyone is searching for.
Semantic Scholar is just getting started. Allen and his team plan to incorporate the full library of medical research into the service by the end of 2017.