Machine learning (ML) and deep learning (DL) content from the past 24 hours. ZDNet has a special section on AI and machine learning. I’ve pulled some of the interesting pieces and linked them in the appropriate sections below. Issues — In Data Science Central, William Vorhies asks: has AI gone too far? The context of his question is a paper
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Machine learning (ML) and deep learning (DL) content from the past 24 hours. Events — Spark Summit East meets in Boston February 7-9 2017. AWS Launches AI Services Amazon Web Services launches three new services: Amazon Rekognition, an image recognition capability Amazon Polly, for text-to-speech Amazon Lex, a chatbot development platform A massive medialanche ensues. Serdar Yegualp applauds. In TechCrunch, Frederic Lardinois touts
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Machine learning (ML) and deep learning (DL) content from the past 24 hours. Events — Spark Summit East meets in Boston February 7-9 2017. Good Reads — From Moor Insights & Strategy, an excellent paper on trends in predictive maintenance, a key application for machine learning. (Update: A reader notes that this is a sponsored paper, which is true, but I have
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Machine learning (ML) and deep learning (DL) content from the past 24 hours. Events — Spark Summit East will meet in Boston February 7-9 2017. Good Reads — In The Next Platform, Nicole Hemsoth explains why Microsoft invests in FPGAs for compute-intensive applications like machine learning. Separately, Nicole investigates Intel’s strategy to integrate the deep learning assets it acquired when it
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ICYMI: Top machine learning (ML) and deep learning (DL) stories from last week. News — Google announces a $4.5 million investment in the Montreal Institute for Learning Algorithms. PR avalanche ensues. — In Investopedia, Richard Saintvilus chronicles the cloud machine learning wars. — Six months after releasing DSSTNE, an internally developed deep learning framework, AWS announces plans to standardize on MXNet.
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Machine learning (ML) and deep learning (DL) content from the past 24 hours. Note to readers: owing to the U.S. Thanksgiving holiday, I do not plan to publish a Roundup on Thursday, November 24 or Friday, November 25. AWS Chooses MXNet Six months after releasing DSSTNE, an internally developed deep learning framework, AWS announces plans to standardize on MXNet. In
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Machine learning (ML) and deep learning (DL) content from the past 24 hours. Events — Spark Summit East will meet in Boston February 7-9 2017. Good Reads — Adrian Colyer summarizes a report from Stanford University covering key topics in artificial intelligence, including large scale machine learning, deep learning, reinforcement learning, robotics, computer vision, natural language processing, algorithmic game theory, IoT,
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ICYMI: Top machine learning (ML) and deep learning (DL) stories from last week. News — On the AWS Compute Blog, Naveen Swamy and Joseph Spisak explain distributed deep learning with the AWS Deep Learning AMI. The AMI supports Caffe, CNTK/Microsoft Cognitive, MXNet, TensorFlow, Theano, and Torch. Product reviewers are underwhelmed, noting the absence of NVIDIA, CUDA, Anaconda or Python3 support. —
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Machine learning (ML) and deep learning (DL) content from the past 24 hours. SC16 Roundup The International Conference for High Performance Computing, Networking, Storage and Analysis (SC16) meets this week, which is why we’re seeing so many HPC announcements. — The folks at The Next Platform capture some highlights: Ben Cotton surveys the program, focusing on topics of interest to programmers:
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Machine learning (ML) and deep learning (DL) content from the past 24 hours. Google Enhances Machine Learning Services Google launches a dedicated team to drive Google Cloud Machine Learning, and announces a slew of enhancements to its services: — Google Cloud Jobs API provides businesses with capabilities to find, match and recommend jobs to candidates. Currently available in a limited alpha. —
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ML/AI 