In the machine learning world, making models run across a variety of mobile phones is notoriously challenging. This is why Fyusion, a visual intelligence company owned by Cox Automotive, has delivered a powerful new open-source library that makes it easy and efficient to run machine learning models on almost any mobile device. Now available on GitHub, this lightweight yet powerful software library called FyuseNet can take a wide variety of machine learning models and write incredibly fast implementation for whichever platform the developer chooses—all while maintaining a lean application.
“At Fyusion, we live at the intersection of high-tech research and pragmatic engineering, bringing big ideas to life in a way that can truly benefit people around us,” said Stephen Miller, Fyusion Co-Founder and Chief Product Officer. “We know how powerful FyuseNet is, as we’ve used it for years in our own work, and we believe that this can be the one beautiful library that everyone uses to accelerate advancements in machine learning.”
Also Read: Acura Names Upstart Auto Retail a Preferred Digital Retail Provider
With stark differences between operating systems, as well as fragmentation across older and newer generations of phones, creating machine learning models for mobile phones has been notoriously inefficient. This has led to innovations mostly being reserved for the $1,000+ flagship phones that are out of the reach of many people.
However, the team at Fyusion is on a mission to democratize machine learning and ensure that these technologies are more accessible to more people. That’s why it was important to them to open access to FyuseNet, as its lightweight implementation makes it compatible with the majority of devices—regardless of manufacturer or specific processor details—even when there’s no network connectivity available. Created in 2016 for internal use, FyuseNet has been iterated on for years within Fyusion before making its inaugural appearance on GitHub this year.
SOURCE: PR Newswire