Parasoft is showcasing its latest product innovations at embedded world Exhibition, booth 4-318, including new GenAI integration with Microsoft Visual Studio Code (VS Code) to optimize test automation of safety-critical applications while reducing development time, cost, and risk.
Cloudera announced a preview of a new, next-generation, cloud-native machine learning platform powered by Kubernetes.
The upcoming Cloudera Machine Learning expands Cloudera's offerings for enterprise self-service data science. It delivers fast provisioning and autoscaling as well as containerized, distributed processing on heterogeneous compute. Cloudera Machine Learning also ensures secure data access with a unified experience across on-premises, public cloud, and hybrid environments.
Cloudera Machine Learning combines data engineering and data science, on any data, anywhere. In addition, it breaks down data silos to simplify and accelerate the end-to-end machine learning workflow.
Cloudera Machine Learning enables enterprises to accelerate machine learning from research to production – empowering users to easily provision environments and scale resources so they can spend less time on infrastructure and more time on innovation.
Capabilities include:
- Seamless portability across private cloud, public cloud, and hybrid cloud powered by Kubernetes
- Rapid cloud provisioning and autoscaling
- Scale-out data engineering and machine learning with seamless dependency management provided by containerized Python, R, and Spark-on-Kubernetes
- High velocity deep learning powered by distributed GPU scheduling and training
- Secure data access across HDFS, cloud object stores, and external databases
"Making teams more productive is essential to scaling machine learning capabilities in the enterprise. This requires a new kind of platform to consistently build and deploy models across highly scalable, transparent infrastructure, tapping into data anywhere," said Hilary Mason, GM, Machine Learning at Cloudera. "Cloudera Machine Learning brings together the critical capabilities of data engineering, collaborative exploration, model training, and model deployment in a cloud-native platform that runs where you need it – all with the built-in security, governance, and management capabilities our customers require."
With Cloudera Machine Learning plus research and expert guidance from Cloudera Fast Forward Labs, Cloudera offers a comprehensive approach to accelerating the industrialization of AI for customers.
Cloudera Machine Learning is planned to release in 2019.
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