IBM acquires AlchemyAPI to fatten Watson portfolio
IBM has acquired computing services provider AlchemyAPI to broaden its portfolio of Watson-branded cognitive computing services.
IBM has acquired computing services provider AlchemyAPI to broaden its portfolio of Watson-branded cognitive computing services.
Scan through the news announcements in the world of enterprise software lately, and there's a good chance you'll notice an overriding theme. It focuses on analytics, and it's all about putting the power of that once-highly specialized function within the hands of a broader spectrum of business users.
Western Australia is refining its search for minerals and resources using mapping and tracking technology that is tailored for smartphones and mobile devices.
Western Australia is finalising the blueprint for open government, together with a focus on being “open by default” and streamlining access to untapped data and services.
Capturing public conversations around the world in real time, Twitter could be a valuable source of intelligence for the business world, so IBM is creating new ways to derive potentially valuable information from this massive, sprawling data set.
Apache Spark, <a href="http://www.infoworld.com/article/2852235/hadoop/review-spark-lights-a-fire-under-big-data-processing.html?nsdr=true">the big data processing technology for iterative workloads</a> that is growing in popularity, is about to add capabilities for DataFrames and the R language as part of two upcoming upgrades.
One of the core challenges in any big-data effort is combining data from multiple sources and turning it into something useful.
Bowing to customer pressure, enterprise software and services vendor Pivotal will release as open source the remainder of its software suite for analyzing data.
A number of the largest big data vendors, including IBM, Hortonworks and Pivotal, have banded together to specify a unified base platform for the open source Hadoop data processing software.
Hewlett-Packard has devised a way to run programs written in the R statistical programming language against data sets that span more than one server, potentially paving the way for large-scale, real-time predictive analytics.
Big data may have just crested the wave of inflated expectations and be barrelling towards the trough of disillusionment, at least if you're following along with the Gartner Hype Cycle.
If you use Siri, Netflix or even Google AdWords, you've already sampled machine learning, whether you realize it or not. Such technology can help companies figure out what you want, what you like, and what you might like in the future.
A few years ago I was the CTO and co-founder of a startup in the medical practice management software space. One of the problems we were trying to solve was how medical office visit schedules can optimize - everyone's - time. Too often, office visits are scheduled to optimize the physician's time, and patients have to wait way too long in overcrowded waiting rooms in the company of people coughing contagious diseases out their lungs.
As each new generation of computer processors arrives with a larger number of computing cores, computer scientists grapple with how best to make use of this proliferation of parallel power.
A streaming analytics engine developed by Microsoft Research is giving advertisers on the company's Bing Web search service more timely analysis on how their ad campaigns are faring, according to the company.