2 years ago

Category: Software, Business, Data, artificial-intelligence

Following its https://www.redhat.com/en/blog/introducing-red-hat-openshift-data-science earlier this year, Red Hat has released https://www.redhat.com/en/technologies/cloud-computing/openshift/openshift-data-scienceas a “field trial”. According to https://www.linkedin.com/in/stevenhuels, senior director for AI product management at Red Hat, AI/ML is nothing new for Red Hat, and the origins of Red Hat OpenShift Data Science lie in the company’s experience building AI/ML features into its own platform, with things like Red Hat Insights. Eventually, Red Hat took that experience and codified it into the https://opendatahub.io/ open source project, but Huels explained that Red Hat’s customers were looking for a managed service they could buy that would provide these capabilities.

Red Hat OpenShift Data Science is built upon a subset of the components offered in Open Data Hub, such as JupyterLab, Tensorflow, PyTorch, SciKit, Panda, and NumPY, which it then integrates with more deeply in Red Hat OpenShift and offers SRE support around, as part of the managed service.

This latest version of Red Hat OpenShift Data Science comes with several new features, including the https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-analytics-toolkit.html and support for https://marketplace.redhat.com/en-us/products/openvino, as well as new integrations for https://www.anaconda.com/products/commercial-edition, https://www.ibm.com/cloud/watson-studio, https://www.seldon.io/tech/products/deploy/, and https://www.starburst.io/platform/starburst-galaxy/.