Tag Archives: MapR

Big Analytics Roundup (September 19, 2016)

Many thanks to Australia’s Dez Blanchfield for his contributions to this roundup. We set out to create a special “Australia/APAC” edition; however, most of the stories have a global interest: chips are chips and deep learning is deep learning wherever you live. We did find this story, profiling a Tasmanian oyster farm that uses Microsoft’s IoT hub. Well, that’s embarrassing. MapR’s

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Big Analytics Roundup (August 8, 2016)

So, Apple acquires Turi for $200 million. Hopefully, Apple did not pay for brand equity. Bridget Botelho argues that businesses must either disrupt or be disrupted, and outlines the role of machine learning. Someone should write a book about that. Conference Announcements — Flink Forward announces the schedule for its second annual event, to be held September 12-14 in Berlin. —

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Big Analytics Roundup (August 1, 2016)

There are two big stories this week: Apache Spark 2.0 and Apache Mesos 1.0. There’s also a new release from Kylin, and a nice crop of explainers. IEEE Spectrum publishes its third annual ranking of top programming languages, based on twelve metrics drawn from Google Search, Google Trends, Twitter, GitHub, Stack Overflow, Reddit, Hacker News, CareerBuilder, Dice, and the IEEE

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Big Analytics Roundup (May 23, 2016)

Google announces that it has designed an application-specific integrated circuit (ASIC) expressly for deep neural nets. Tech press goes bananas. The chips, branded Tensor Processing Units (TPUs) require fewer transistors per operation, so Google can fit more operations per second into the chip. In about a year of operation, Google has achieved an order of magnitude improvement in performance per watt for

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Big Analytics Roundup (April 11, 2016)

Top story of the week is NVIDIA’s new DGX-1 deep learning chip; scroll down for more on that. We have three roundups from Strata + Hadoop World, Rashomon style: Alex Woodie reports six takeaways: Kafka, Spark, Hadoop, Cloud, machine learning, mainframes. Jessica Davis recalls four things: comedian Paula Poundstone, MapR, public data sets, AI. Nik Rouda recaps five things: Spark, machine learning,

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