The Paradigm Shift That Will Power a New Era of AI Innovation - Coruzant Technologies

Deep learning is set to transform entire industries and create new opportunities on a scale not seen since the Industrial Revolution in the 19th century. But while recent years have seen breakthrough innovation in deep learning, developers still face formidable obstacles in creating effective deep learning models, particularly when aiming to put them into production. Amid major advances in the field of deep learning, thousands of companies and startups are building products and services that rely on this technology. Building the deep neural models needed to power business applications requires not only deep expertise in the field, but also substantial time and resources devoted to critical tasks like model design, training, quality testing, deployment, maintenance and periodic updates, and revisions. Given that deep learning's value proposition promises to unlock new efficiencies, the expensive and cumbersome process of actually creating and deploying deep learning models has been a sticking point for many organizations seeking to leverage the technology.