I recently attended a meeting of government and industry HPC leaders where one topic of much discussion was why so many universities have started “Data Science” programs but with the exception of a small number of universities, are not actively training students in HPC and parallel programming. …
Although traditional relational databases will not be disappearing anytime soon, for a growing set of data-intensive problems, graph-based approaches are still finding a fit, even well after the boom from web-scale workloads forced companies like Google, Facebook, and others that direction. …
Even though the buzz around neural networks, artificial intelligence, and machine learning has been relatively recent, as many know, there is nothing new about any of these methods. …
Teradata is bringing its flagship data warehouse to Amazon Web Services. …
Over the last few years, every major technology company has made a grand movement to embrace data in much the same way they did in the mid-2000s with cloud. …
“Machine learning connects supercomputing to consumers; its impact will be felt everywhere.” …
Document databases are an integral part of the application stack, but they often have scalability issues and they tend to end up off to the side of the Hadoop systems that are increasingly being used as a the repository of record for all kinds of data. …
The Spark in-memory processing framework that came out of the AMPLab at the University of California at Berkeley is hotter than hot. …
If one were to look at the approximate results from various deep learning tasks; from image classification to speech recognition and beyond, the stand-by quote from Bayesian statistics that “probability is orderly opinion, and that inference from data is nothing other than the revision of such opinion in the light of relevant new information,” takes on added weight. …
If Google knows a lot about one thing, it is that developers do not want to spend a lot of time setting up infrastructure just so they can create applications that chew on lots of data to run the business. …
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