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takyon writes:

Ray Kurzweil, populist futurist and a director of engineering at Google, has an article highlighting three developments in machine learning:

Google DeepMind in London said it has developed a way to teach machines to read natural-language documents and comprehend them, and like Watson, answer complex questions with minimal prior knowledge of language structure — at least for CNN and Daily Mail websites. As noted by the researchers in an arXiv paper (open access), these websites have summaries (such as bulleted lists) and paraphrase sentences. The researchers were able to use these for creating context–query–answer triples for each document. In the process, they generated two new corpora (collections of data) of roughly a million news stories with associated queries to serve as training sets.

Facebook has launched Moments, an app that uses facial recognition technology to group the photos on your phone based on when they were taken and, using facial recognition technology, which friends are in them. You can then privately sync those photos quickly and easily with specific friends, and they can choose to sync their photos with you as well... But an experimental algorithm created by Facebook's FAIR lab can recognize people in photographs even when it can't see their faces. Instead it looks for other unique characteristics like your hairdo, clothing, body shape and pose, New Scientist notes.

Amazon has developed a machine learning algorithm that will "learn which reviews are most helpful to customers" — that is, which reviews are real and which ones are fake. (Amazon sued a number of websites that specialized in creating fake Amazon reviews in April.) Amazon will give greater weight to newer, more helpful and verified customer reviews and ratings (their 5-star system). Amazon Web Services began offering its Amazon Machine Learning service in April to make "it easy for developers of all skill levels to use machine learning technology... without having to learn complex ML algorithms and technology."