IBM Marries R Programming Language to Watson

Mike Vizard
Slide Show

5 Trends Impacting the Future of Machine Data Intelligence

One of the most important constituencies in the development of advanced cognitive computing applications these days is the data scientists trying to combine massive amounts of data and various types of algorithms to automate a particular task or process. Today, IBM, in partnership with Columbus Collaboratory, announced they have jointly developed a software development kit (SDK) that makes it simpler to integrate applications developed using the R programming language with the IBM Watson cognitive computing platform.

While IBM has always exposed Watson application programming interfaces, Rob High, chief technology officer for Watson at IBM, says CognizeR is an SDK that eliminates the need for a developer to write as much code to invoke Watson services.

“We’ve been creating SDKs for a number of programming languages,” says High. “But this is the first time we have one for the R programming language.”

Widely used in the data science community, the R programming language is utilized to create any number of models employing algorithms. High says IBM envisions data scientists will now be able to more easily incorporate the cognitive computing capabilities of Watson to make it possible to apply those models against massive amounts of data.

In general, cognitive computing is at something of a crossroad. Platforms such as Watson clearly have a major role to play in advancing, for example, diagnostics and medical research. However, a growing body of critics complains that IBM and other providers of cognitive computing platforms are overstating the capabilities of what can be achieved. Cognitive computing, they argue, is a long way from actual artificial intelligence.

High says that when it comes to advances being pioneered by Watson, there is always going to be some “cognitive dissonance” concerning its true capabilities. Watson can not only analyze more data than any single human could ever hope to consume; it can infer an answer to any given question. What it can’t do is come up with the question that needs to be asked in the first place.

Nevertheless, it’s also clear that the ability to answer questions that in many instances were previously unfathomable will have a major societal impact, ranging from breakthroughs in science to the elimination of some existing job functions. The challenge now is figuring out how best to absorb those changes in a way that improves the overall human condition.

Add Comment      Leave a comment on this blog post

Post a comment





(Maximum characters: 1200). You have 1200 characters left.



Subscribe to our Newsletters

Sign up now and get the best business technology insights direct to your inbox.