MapR Technologies the provider of the Converged Data Platform enabling organizations to create applications that fully integrate analytics with operational processes in real time, today announced that NorCom, a full-chain supplier for big data solutions, has selected the MapR Converged Data Platform to serve as a foundation for its autonomous driving applications that leverage deep learning technologies. The partnership enables joint customers to deploy deep learning frameworks that can provide fast and reliable analysis in critical compute environments.
“We help German automotive giants Audi and Daimler harness the power of deep learning in order to achieve their goal of building autonomous vehicles. In MapR, we found the perfect platform to scale our deep learning efforts using distributed storage and compute.” said Dr. Tobias Abthoff, member of the executive board, NorCom.
NorCom leverages a purpose-built deep learning framework for the automotive industry. To fully take advantage of it, they needed a way to efficiently manage the massive data sets generated by sensors and cameras in self-driving cars. Running containerized deep learning applications on the MapR Platform provided the required speed, scale and reliability to successfully analyze continuous data in an autonomous driving environment and achieve the benefits of deep learning.
“Autonomous driving applications are a perfect example of how a scalable and reliable data platform can successfully enable deep learning in a real-time production environment. Volumes of data can quickly outgrow traditional data management approaches. The MapR Platform provides a modern and flexible foundation for deploying applications that help organizations innovate, compete and thrive.” said Anoop Dawar, vice president, product marketing, MapR Technologies
A key reason NorCom selected MapR is the ability of the platform to support machine learning applications in Docker containers, which helps to scale the applications with agility. The MapR Converged Data Platform works with multiple deep learning frameworks, including TensorFlow and Caffe, providing organizations the flexibility to choose the best suited framework for their use case. As a single platform across all data centers, cloud deployments, and edge clusters, the MapR Platform makes it easier to roll out machine learning models so that they can be applied to newly created data anywhere across the data fabric. Moreover, the newly created data can be immediately added to the training data set because both reside on the same platform. This simplifies the important goal of continuously improving the accuracy of machine learning models.
NorCom benefits from the ability of the MapR platform to support real-time processing of a broad variety of data types, including files, documents, images, database tables and data streams. The MapR platform is engineered to meet the most stringent speed, scale and reliability requirements within and across multiple edge, on-premises and cloud environments. The platform is designed to serve as a system of record and to support transactional workloads, with comprehensive high-availability, data protection and disaster recovery capabilities.