What do you get when you cross machine learning with edge devices and mesh networks for predictive analytics? Edge intelligence software that cuts cloud and data storage completely out of the equation. In this first episode of the monthly Conversational Interface podcast, we talk to Simon Crosby, CTO of a new edge intelligence software company called Swim.AI. Its software, Swim EDX, is a mashup of edge computing and machine learning that uses edge data and runs locally on existing edge devices, such as sensors, in a mesh architecture. The software born of this complicated mix of technologies addresses the problem of what to do with all of the real-time data generated by edge devices and sensors, and how to use that data to provide fast, local analytics to governments, manufacturers and companies in other sectors that need it.
In the move to hybrid IT, enterprises are experiencing the familiar challenge of technology management needing to catch up with new compute innovation. Cloud adoption (public and private) is occurring at a rapid pace with cloud and big data on the rise, and IT teams do not have the management tools necessary to extract value from data in a way that is operationally or economically efficient.
Today AWS in partnership with WP Engine is announcing the release of an Amazon Polly plugin for WordPress. The sample plugin enables WordPress creators to easily add Text-to-Speech capabilities to written content. As voice interaction becomes more common, it's essential to provide your website's content in audio formats. And, visitors who are drawn to your websites by voice capabilities can now consume your content through new channels, such as inline audio players and mobile podcast applications. Now your readers and listeners can listen to your posts, even while they are away from the screen – driving, riding a bike, or even jogging.
Big data management and analytics saw plenty of commotion last year, as bleeding-edge users dug deeper into machine learning, streaming architectures gained attention and cloud computing exercised greater overall influence. There's little indication things will slow down in 2017. The emphasis on cloud for data has been both gradual and sudden. Ten years ago, in the early days of cloud computing, there were more than a few users who held that data would probably never go to the cloud in great portion. Recent years have seemed to dispel that notion and, in 2016, cloud and data got tangibly closer.