Getting the most out of AI with open source and Kubernetes - Seguridad Mania.com - España y América Latina

Red Hat has been instrumental in driving many open source community efforts around artificial intelligence and machine learning (AI/ML) technologies for more than 6 years through the Open Data Hub project. Open Data Hub is a fully open project that supports end-to-end AI/ML workflows running in containers on Red Hat® OpenShift®, a Kubernetes-powered application platform. Many organizations have used some of the technologies curated in the Open Data Hub project—such as Jupyter, TensorFlow, Pytorch, Kubeflow, and Ray—to jumpstart their own do-it-yourself efforts aimed at creating a core data science platform to build intelligent applications. In addition to working closely with the open source community, Red Hat has responded to numerous requests to offer a paid and supported version of Open Data Hub. This has resulted in Red Hat OpenShift Data Science, a powerful platform for building, deploying, and monitoring AI/ML models and applications across on-premise, public cloud, and edge environments. Red Hat continues to invest in Open Data Hub and refine the upstream technologies it continues to curate on Red Hat OpenShift, while building out experimentation and MLOps capabilities that feed into OpenShift Data Science. In this webinar, we’ll take you through how to get the most out of open source AI, introduce you to OpenShift Data Science, and provide a roadmap for planned future investments by Red Hat for AI on Red Hat OpenShift. Our webinar topics include: Open source AI: Best practice guidance on taking advantage of these technologies Where Red Hat will focus its future efforts around Open Data Hub How a commercial version can help offload the curation and integration of these technologies from you to Red Hat Some best approaches to adopting OpenShift Data Science while maintaining your current open environment