IBM Watson supercomputer strives to achieve continuous value

The IBM Watson supercomputer simultaneously depends on and drives DevOps.

It relies on DevOps principles because a self-learning cognitive system needs continuous monitoring and continuous improvement to keep up with the volume of data being analyzed. Without DevOps Watson would struggle to correlate, learn, and adapt from the information it analyzes.

Watson is also a powerful DevOps tool. A computer that can process natural language queries and formulate intelligent responses is very effective for automating intensive tasks like ingesting and analyzing massive amounts of data to streamline productivity and free up human resources for other tasks.

I wrote about the relationship between Watson and DevOps in this blog post:

While attending IBM InterConnect in late February I had an opportunity to sit in on a press conference. The focus of the press conference was primarily around IBM’s efforts related to hybrid cloud solutions, but the thing that caught my attention was a little tidbit mentioned almost in passing about an innovative way students at the University of Texas Austin had applied the power of the Watson supercomputer.

Robert LeBlanc, senior VP of IBM Cloud, and a handful of other executives shared IBM’s vision for hybrid cloud and big data analytics with the media. The press conference ranged from data sprawl, to data visibility, to security and performance. The group talked about a focus on developers and the importance of open standards and more.

Then there was the bit about Watson and the University of Texas. For those who may not know, Watson is a cognitive computing system. It is a supercomputer with an artificial intelligence component that enables is to analyze massive volumes of data, understand complex queries posed in natural language, and respond with evidence-based answers. It learns as it goes.

Watson University Competition

IBM has enlisted the support of companies and organizations around the world to help develop new applications for Watson and push the envelope of its capabilities. One of the programs that helps drive innovation with Watson is the Watson University Competition.

Students participating in IBM’s Watson University Competition were directed to identify and solve an industry-specific challenge using Watson. Students had to work as a team to identify and input relevant data into Watson in order to train the supercomputer to answer questions related to the issue being solved. The students must then develop an app and supporting business plan targeting their chosen industry.

The UT Austin team won the competition with an app called CallScout. The purpose of the app is to help Texas residents find information about social services and programs in their local area. Many Texas residents depend on state resources for housing, healthcare, transportation and other vital functions, but wading through government websites and other information is confusing and makes it difficult for residents to find the information they need. The CallScout app integratesl hours of service, route and map information and other relevant data, and it can automatically deliver push notifications when important details change.

“This is more than a school project for us – it’s about creating a sustainable business that addresses one of the key challenges we all face as Texas residents,” said Bri Connelly, team leader and undergraduate Computer Science student at the University of Texas at Austin. “The opportunity to directly impact citizens of our home state was a huge driving force in our work.”

Read the complete story at DevOps.com: IBM’s Watson sits at the crossroads between DevOps and Big Data.