John Platt, a Distinguished Scientist at Microsoft Research today blogged about the history of machine learning at Microsoft. Machine Learning has become a buzz word these days, thanks to consumer facing features such as Cortana, Google Now, etc. Microsoft is using the concepts of machine learning for over 20 years starting in 1992. It is being used in content-based spam detector, speech recognition, predictive analytics to the Commerce Server product, Data mining product in SQL Server, and more. More recently, Microsoft announced Microsoft Azure ML which will allow users to create models that can be deployed to the cloud, rather than being restricted to one particular data management platform (such as SQL). The story of ML at Microsoft started in 1992. We started working with Bayesian Networks, language modeling, and speech recognition. By 1993, Eric Horvitz, David Heckerman, and Jack Breese started the Decision Theory Group in Research and XD Huang started ...

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After selling the Devices and Services division to Microsoft, Nokia is now trying to  build a great location platform out of HERE. Last month, they announced that they have acquired Desti, an SRI international spin-off that uses artificial intelligence and natural language understanding to create deep knowledge of destinations by reading everything about them, and understands users’ natural language, so they can be specific and get the best results, immediately. Today, they announced that they have acquired Medio systems for an undisclosed sum. Medio leverages predictive models to optimize mobile customer acquisition, retention and  monetization using a cloud-based infrastructure for collecting and analyzing customer activity data. Nokia HERE team believes that building on Medio’s ‘smart data’ asset enables HERE to create contextual maps and location services that change according to the situation to provide highly personalized and predictive experiences for people and businesses. Read the full press release below, Berlin, Germany ...

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David Rothschild, an economist from Microsoft Research New York City predicted the winners of the Oscars in 2013 using various data available on the web. He was accurate with his prediction in 19 of the 24 Academy Awards categories. For Oscars 2014, he posted his predictions for 24 categories weeks back. The Oscars 2014 event just got over and what about his accuracy of prediction this year? He correctly predicted 21 out of 24 categories which is a great improvement over last year. The three categories which he got wrong were Best Animated Short Film, Best Documentary Feature and Best Live Action Short Film. I guess the lack of enough data is one of the reason behind the above three errors. David commented the following on the results, There are two ways to judge accuracy. First, and most obvious, you want a small error. Correctly predicting 21 out of 24 ...

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