We are always driven to try to do smarter things faster. It’s human nature. In our data centers, we layer machine learning algorithms over big and fast data streams to create that …
When we want to start computing at biological scales and speeds – evolving today’s practical machine learning forward towards long-deferred visions of a more “artificial intelligence” – we’ll need to …
Machine learning is the force behind many big data initiatives. But things can go wrong when implementing it, with significant effects on IT operations.
Unfortunately, predictive modeling can be fraught with peril …
At this month’s Hadoop Summit 2015 I noted two big trends. One was the continuing focus on Spark as an expansion of the big data analytical ecosystem, with main sponsor …
We are seeing convergence everywhere in IT these days. AccelOps shows how convergence in systems management offers many of the same kinds of values as it does in other areas …
Cloud and on-premises storage are increasingly becoming integrated. This means cloud tiering is just another option available to storage administrators. Organizations aren’t likely to move 100% of their data into cloud services, …
