Stay on target Robot Dog Astro Can Sit, Lie Down, and Save LivesMIT’s AI Knitting System Designs, Creates Woven Garments It’s not exactly news that women are overlooked and underappreciated.But thanks to a new machine learning system, female scientists, technologists, engineers, and mathematicians (among other professionals) will finally get their digital due.San Francisco-based Primer is using artificial intelligence to fill in existing gaps in human-generated knowledge—starting with notable ladies like Canadian roboticist Joelle Pineau, addiction treatment researcher Miriam Adelson, and Evelyn Wang, head of MIT’s MechE department.None of whom, until this month, had articles on English Wikipedia. Yet, someone took the time to curate a “list of people who have lived at airports” for the online encyclopedia.“I didn’t discover those people on my own. I used a machine learning system we’re building,” John Bohannon, director of science at Primer, wrote in a recent blog post. “It discovered and described them for me.”(And the Internet created entries for him.)“It does this much as a human would, if a human could read 500 million news articles, 39 million scientific papers, all of Wikipedia, and then write 70,000 biographical summaries of scientists,” Bohannon added.It’s called Quicksilver. And it’s an homage to Neal Stephenson’s Baroque Cycle novel series, which imagines technology that captures all human information “in a vast encyclopedia that will be a sort of machine, not only for finding old knowledge but for making new.”Trained on 30,000 English Wikipedia articles about scientists, their Wikidata entries, and more than 3 million sentences from news documents, as well as the names and affiliations of 200,000 authors of scientific papers, Quicksilver produced shocking results.“In the morning we found 40,000 people missing from Wikipedia who have a similar distribution of news coverage as those who do have articles,” Bohannon said. “Quicksilver doubled the number of scientists potentially eligible for a Wikipedia article overnight.”Launched more than 17 years ago, Wikipedia remains one of the largest and most popular general reference works on the Internet. But it takes a lot of upkeep; every article must be meticulously cited and regularly updated—forever.Despite a decade of attempts, no one has managed to crack the code for computer-generated passages. And Primer doesn’t plan to, either.Rather than use the World Wide Web “as an academic testbed for summarization algorithms,” Bohannon said, the firm is working on a system “that can be used for building and maintaining knowledge bases” like Wikipedia.As an experiment, Primer is publishing a sample of 100 short Quicksilver-generated summaries of scientists missing from Wikipedia.“We’re curious how long it will take before someone creates their articles,” Bohannon said.In the span of about a week, all three women mentioned in his blog have since been covered on the site. Three down, tens of thousands to go.To learn more about AI click here.Let us know what you like about Geek by taking our survey.