Movidius ups the ante for trade show trinkets by releasing what journos describe as supercomputing, neural computing power, vision processing, deep learning, and artificial intelligence on a USB drive. Roundup here. Last November, IBM’s Paul Zikopoulos snarked at Cloudera for not supporting SparkR. Cloudera’s Sean Owen, responding to a query in the Cloudera Community, notes that SparkR “does not work with other resource managers,” and
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In hard news this week, Storm hits a milestone with Release 1.0, Google releases TensorFlow 0.8 with distributed computing support, and DataStax announces DataStax Enterprise Graph. And, following on NVIDIA’s DGX-1 announcement last week there are a number of items on Deep Learning featured below. Deep Learning — Adrian Colyer summarizes a paper that summarizes 900 other papers on Deep Learning. —
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Strata + Hadoop World sparks a number of commercial announcements: AtScale has a new release, Microsoft previews R Server on HDInsight, and IBM puts Spark on a mainframe, FWIW. We also have a nice harvest of explainers and perspectives. Slides from Strata available here. The folks at Domino Data ask: Is XGBoost 10X faster than H2O? We’ll never know the answer, since they
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Dell and Silver Lake Partners announce plans to buy EMC for $67 billion, a transaction that is a big deal in the tech world, and mildly interesting for analytics. Dell acquired StatSoft in 2014,but nothing before or since suggests that Dell knows how to position and sell analytics. StatSoft is lost inside Dell, and will be even more lost inside Dell/EMC.
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Announcements timed to coincide with Strata NYC 2015 drive the news this week. The single most interesting item for Big Analytics is the O’Reilly 2015 Data Science Survey, which warrants a post of its own. Two key points: Data scientists still use SQL, Excel, Python and R. (Doh!) Data scientists who spend time in meetings and presenting results of analysis earn
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So I guess Spark really is enterprise ready. Nick Heudecker, call your office. There are several key themes coming from the Summit: Spark Continues to Mature Spark and its contributors deserve a round of applause. Some key measures of growth since the 2014 Summit: Contributor headcount increased from 255 to 730 Committed lines of code increased from 175K to 400K
Read moreThe team at AMPLab has announced a developer preview of SparkR, an R package enabling R users to run jobs on an Apache Spark cluster. Spark is an open source project that supports distributed in-memory computing for advanced analytics, such as fast queries, machine learning, streaming analytics and graph engines. Spark works with every data format supported in Hadoop, and supports YARN 2.2. SparkR exposes the Spark
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