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‘Natural language understanding’ poised to transform how we work

Technology from Primer, a San Francisco artificial intelligence start-up, is already used by unspecified intelligence services to read through written material in an effort to identify trends and significant events. The results help guide human analysts to focus on what is important. The same software is used by retailer Walmart, where analysts constantly monitor a large number of product markets to identify opportunities and risks in the company’s supply chain.

Taming arXiv w/ Natural Language Processing with John Bohannon

In our conversation, John and I discuss his work on Primer Science, a tool that harvests content uploaded to arxiv, sorts it into natural topics using unsupervised learning, then gives relevant summaries of the activity happening in different innovation areas. We spend a good amount of time on the inner workings of Primer Science, including their data pipeline and some of the tools they use, how they determine “ground truth” for training their models, and the use of heuristics to supplement NLP in their processing.

How AI Helps The Intelligence Community Find Needles In The Haystack

Today, Primer is coming out of stealth. The 35-person startup, which has raised $14.7 million to date and recently closed a Series A round of funding, has developed a machine learning system that is able to quickly search through tens of millions of data sources–news articles, academic papers, social media posts, and so on–to surface the kinds of information that is essential to both intelligence analysts and corporate analysts alike.