To build intelligence quickly into systems and to accelerate Deep Learning adoption and enrich the ecosystem
All over the world technology companies and start-ups trying to create products that use Artificial Intelligence are racing to build neural networks. By their very nature however, neural networks are complex and call for Deep Learning. Arya.ai steps in to offer deep learning tool, Braid, to speed up this process by leaps and bounds.
Building neural networks, which are not unlike actual human brains with their complex layers, is a resource-intensive, expensive and time consuming process. And yet, these need to function flawlessly at large scale to handle tasks like speech and language processing, image processing, intelligent virtual assistants and even self-driving cars. Braid is offered, free and open source, to companies that use research scientists and technologists developing these networks.
While several developer platforms and tools exist to develop neural networks, Braid has the singular advantage of being flexible, customisable, and modular, a meta-framework that works with operating systems for Deep Learning. Braid is also simple and scalable for use with networks that need the handling of many data points at large volume.
Illustrating with an example, Vinay Kumar Sankarapu, CEO and founder of Arya.ai, said that for AI to understand, say, medical radiology reports, a neural network with millions of neurones trained and defined into the architecture would be needed to learn the task. “Currently, developing applications on these frameworks needs substantial resource investments in terms of specialized skills and long cycle times. But now, with Braid, it is easy to start up development immediately and deploy the tool.”
Braid is designed for rapid development and to support arbitrary network designs. It allows for quick experimentation without having to worry about the boilerplate components of the code. With Braid, developers can not only customize but also add to existing neural layers while maintaining the simplicity of code. Braid is available for download at http://braidnn.org/
