Machine conquered man when Google’s AlphaGO defeated the top professional Go player, but the evolution of deep learning didn’t end with the game. Baidu improved speech recognition from 89% to 99% and deep-learning jobs grew from practically zero jobs in 2014 to around 41,000 jobs today.
Deep learning is currently at the Peak of Inflated Expectations of the Gartner Hype Cycle, but its evolution from edge technology to a key component of analytics is one of five Gartner predictions for 2017.
Despite seemingly endless promises in the world of data analytics, integrating the data can be a challenge. Automated tools such as deep learning and natural-language generation work well with the correct data, but if the data is not so easy to integrate, it will require professional data integrators and scientists to effectively use these new tools.
“We will see a blend of professional data integrators and data scientists — who can use this technology to become more efficient — along with a small army of citizen data scientists and citizen data integrators who will be recruited to fill more formal or semiformal roles,” said Peter Krensky, senior research analyst. “Data and analytics leaders should commit to leveraging a cross-functional team and the use of sandboxes to help reduce the risk that less-skilled workers will get into trouble.”