Bragi Introduces Bragi Intelligent Edge Software Suite featuring Bragi nanoAI

February 26 2018, 04:00
After 4 years of development, Bragi has made a breakthrough in ultra-efficient artificial intelligence and says it is ready to deliver the first edge computing AI suite. During Mobile World Congress 2018, in Barcelona, Bragi, the company behind The Dash hearable, now the world’s first intelligent Edge Headphone, announced a B2B offer of Bragi nanoAI as a software solution, which the company says helps to overcome major challenges of the current IoT architecture.
 

With Bragi Intelligent Edge, and its software suite formed by the building blocks BragiOS, nanoAI, BragiNET and Hardware Reference Design, Bragi goes a step beyond the consumer electronics business and offers a flexible platform centered around machine learning techniques, which will enable various industries to reduce efforts, time and money regarding embedded development, deployment and maintenance of AI on the edge.
 
The software suite enables manufacturers to gain deeper insights into the usage and needs of their users, which will enable new services and much better user experiences. The technology can be applied in multiple application areas, and is particularly relevant for mobile devices, connected vehicles, wearables, sports, and healthcare. As an example, Bragi Intelligent Edge can be used in sports, connecting all sensors from wearables, wearables like The Dash Pro, or the player’s smartphone, creating a contextual mesh sensing network. Bragi Intelligent Edge could be used to guide and improve the player’s performance. 

Led by Chief Scientist Dr. Friedrich Förstner (Ph.D. in Neuroinformatics), a team has worked unceasingly to embed intelligence on IoT devices with the world’s most efficient AI framework. The growth of the Internet of Things (IoT) and the upcoming trend towards more immersive and interactive user interfaces will flip the center of gravity of data production and computing away from central data centers and out to the edge of IoT. The role of Bragi nanoAI refers to a flexible ultra-efficient framework around novel agile machine learning techniques and massively compressed neural networks that enables ultra-efficient AI on IoT devices such as meters, medical devices, wearables and cars with lowest latency, offline capability and best privacy. 

Bragi nanoAI can even simultaneously span across thousands of sensor-enabled IoT devices for collaborative sensor processing without involving a cloud service. Bragi nanoAI is a pure software solution that can be executed on RTOS, Linux, Windows, Android and iOS devices as well as Bragi OS enabled devices.

This revolutionary approach dates back to BRAGI The Dash, the first true wireless intelligent headphones, whose conception was to go beyond the delivery of high fidelity audio by facilitating leading performance tracking and natural user interfaces. The Dash was designed as a development platform for BRAGI Intelligent Edge. Twenty-seven different embedded sensor streams coupled with embedded storage, enabled BRAGI to fast track the development of Bragi Intelligent Edge in real life environments.
 
Nikolaj Hviid Founder and CEO of Bragi.

“Bragi has focused on ultra-efficient sensor processing in the smallest footprint possible. As a reference Bragi nanoAI processes 27 high frequency sensor streams for automatic activity tracking, heart rate extraction, tracking steps, cadence, breaths, distance with just 16KB of memory and using less than 1% of processing resources on an ARM M4F@26MHz processor. Enterprises can dramatically increase the intelligence locally on the edge computers while reducing or even removing cloud costs,” says Nikolaj Hviid Founder and CEO of Bragi.

BRAGI nanoAI is added to Bragi Intelligent Edge Suite formed by the building blocks of BragiOS and BragiNET. The power of nanoAI, and the software suite Bragi Intelligent Edge enables industries to reduce time and cost to market. This new offer is rolled out in a beta program and is now open for reference projects.
www.bragi.net
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