SANTA CRUZ, CA, January 10, 2018 /24-7PressRelease

Software developers are adopting and using artificial intelligence and machine learning by the millions, according to Evans Data's newly released Global Development and Demographics Study. Twenty-nine percent of developers worldwide, or 6,452,000 in all, are currently using some form of AI or ML and an additional 5.8 million expect to within the next six months. Others expect to incorporate AI or ML techniques later in the future, with only 18%, or slightly less than 4 million, having no plans to ever use these technologies. The Asia-Pacific region is the strongest with almost 3 million developers currently using these technologies.

The Global Developer Population and Demographic Study, now in its 25th edition, is the definitive developer population estimate, updated every six months. The result of extensive secondary research, the study finds 22 million developers worldwide with projections to reach 26.1 million within five years. Global survey data laid atop the population estimates show technology adoption figures worldwide as well as by region.

"There's been a huge uptake for AI and ML technologies by developers." said Janel Garvin, CEO of Evans Data Corp, "Not only have the tools and frameworks multiplied and matured and made adoption much easier, but the developers themselves show a great deal of excitement about using them and enhancing their applications with these new capabilities."

Population trends and estimates cover many different types of development in the most recent study. Additional points discovered in this edition include: 9.9 million developers involved with optimizing security solutions in their organizations, with 1.8 million developers focused on this in North America, and 16.5 million developers working in organizations having a formal DevOps strategy. In DevOps both the APAC and EMEA regions top North America for number of developers.

Source: Evans Data Corporation

Illustration Photo: At the Conference on Neural Information Processing Systems (NIPS) 2017 in Long Beach, California, a team of scientists from the MIT IBM Watson AI Lab unveiled the Moments in Time Dataset, a large-scale, human-annotated dataset of one million, three-second video clips for action recognition created to accelerate the development of AI technologies and models that enable automatic understanding of video content. Led by MIT Computer Science and Artificial Intelligence Laboratory Principal Research Scientist, Dr. Aude Oliva (on right) and IBM Research Scientist, Dr. Dan Gutfreund, the team created the Moments in Time Dataset to encourage advances in video comprehension that will impact multiple industries and applications, such as helping self-driving cars navigate their environment, enabling automatic creation of movie trailers and sports highlights, and assisting the visually impaired with video narration. (credits: John Mottern/Feature Photo Service for IBM / Flickr Creative Commons Attribution-NoDerivs 2.0 Generic (CC BY-ND 2.0))


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