Latest IBM Watson competition works toward building 'big data' workforce

IBM has revealed the winners from its latest round of competition aiming to discover potential use cases for its famous supercomputer, Watson.

Held at the University of Southern California, this marks the third event in a series of competitions held in partnership with academic institutions to both advance interest among students in engineering and math curriculum but also to build "a big data workforce.

IBM reps pointed towards a recent Gartner in a blog post on Monday that 1.9 million "big data jobs" will be created in the U.S. by 2015.

Thus, Big Blue asserted that employers nationwide are going to be looking for candidates who can understand and analyze the trends uncovered from the massive amounts of emerging from mobile devices, social networks, M2M sources, and more.

IBM hinted that employers are also going to be keen on putting big data to use to solve other internal issues, as seen through the second place winner in the IBM-USC competition.

Employee training is a standard operation in corporate environments, but that doesn't mean legacy practices work -- especially in the midst of significant technological shifts.

Thus, the second place team proposed that corporate human resource departments use Watson to optimize employee training based on data related to both the employer's HR needs as well as the employee's career goals.

Citing a study from the American Society for Training and Development that 41 percent of workers at businesses with poor employee training programs leave within the first year, this team argued that a "Watson-powered employee" would be more likely to stay -- and potentially drive higher shareholder value.

For reference, first place went to the team that proposed to use Watson for the discovery portion of legal case because of the system's ability to think like a human, thus saving both time and money while potentially uncovering better results.

Third place was awarded a group that suggested doctors use Watson to identify people who might develop PTSD to line up data about patients' personal stories with experienced pain. The end goal is to offer physicians with more insights about what leads up to PTSD to develop better treatment programs.