This AI Gets Smarter by Surfing the Internet – Robotics Trends

Of the vast wealth of information unlocked by the Internet, most is plain text. The data necessary to answer myriad questions – about, say, the correlations between the industrial use of certain chemicals and incidents of disease, or between patterns of news coverage and voter-poll results – may all be online. But extracting it from plain text and organizing it for quantitative analysis may be prohibitively time consuming.

Information extraction – or automatically classifying data items stored as plain text – is thus a major topic of artificial-intelligence research.

Last week, at the Association for Computational Linguistics’ Conference on Empirical Methods on Natural Language Processing, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory won a best-paper award for a new approach to information extraction that turns conventional machine learning on its head.

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Mike Rawson

Mike Rawson has recently re-awoken a long-standing interest in robots and our automated future. He lives in London with a single android - a temperamental vacuum cleaner - but is looking forward to getting more cyborgs soon.

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This AI Gets Smarter by Surfing the Internet – Robotics Trends

by Mike Rawson time to read: 1 min
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