News

Red Hat Updates OpenShift AI Hybrid AI/ML Dev Platform

• By John K. Waters
• 05/20/2024

Pioneering open-source solutions provider Red Hat announced significant updates to its open hybrid AI and machine learning (ML) development platform, Red Hat OpenShift AI. The updates were designed to make it easier for enterprises to create and deliver AI-enabled apps at scale across hybrid clouds. The company announced the upgrades at the annual Red Hat Summit.

Red Hat OpenShift AI is an open hybrid AI/ML platform built on Red Hat OpenShift. As Red Hat explains on its website, OpenShift AI was built using open-source technologies and "provides trusted, operationally consistent capabilities for teams to experiment, serve models, and deliver innovative apps."

The updates underscore Red Hat’s AI vision for AI and commitment to offering customer choices from the base hardware to advanced tools like Jupyter and PyTorch.

Red Hat enhanced the platform to accelerate innovation and boost productivity, the company says, and to integrate AI into daily business operations through a flexible, scalable, and adaptable open-source platform. Among other things, it supports both predictive and generative models, with or without reliance on cloud environments.

"AI integration into enterprises has shifted from a possibility to a certainty," said Ashesh Badani, senior vice president and chief product officer at Red Hat, in a statement. He emphasized the need for a reliable and adaptable AI platform that boosts productivity, increases revenue, and drives market differentiation. According to Badani, Red Hat OpenShift AI meets the growing demand for enterprise-scale AI, facilitating the deployment of smart applications across the hybrid cloud.

Industry analysts at IDC have pointed out that the transition of AI models from experimental phases to production presents several challenges—things like rising hardware costs, data privacy issues, and a general distrust in sharing data with SaaS-based models. Rapid changes in generative AI also pose difficulties for many organizations aiming to establish a dependable core AI platform that functions both on-premises and on cloud platforms.

IDC has said that, for effective AI utilization, enterprises must update existing applications and data environments, remove barriers between current systems and storage platforms, enhance infrastructure sustainability, and strategically place different workloads across cloud, datacenter, and edge locations.

Red Hat’s AI strategy promotes flexibility across the hybrid cloud, the company says. It allows enhancements to pre-trained or custom models using proprietary data and supports a range of hardware and software accelerators. Red Hat OpenShift AI’s latest upgrades, including the new version 2.9, offer access to the newest AI/ML innovations and an expansive AI-focused partner network. These features address various enterprise needs through features such as model serving at remote locations, improved model serving that supports multiple types, and distributed workloads management for more efficient data processing and model training.

In addition to powering IBM’s watsonx.ai, Red Hat OpenShift AI is being adopted by various industries to spur AI innovation and expansion, including by AGESIC and Ortec Finance.

Red Hat has been at the forefront of the open-source movement for more than three decades, from launching open enterprise Linux platforms with RHEL in the early 2000s to advancing containers and Kubernetes for open hybrid cloud and cloud-native computing with Red Hat OpenShift.

This momentum continues as Red Hat supports AI/ML strategies across the open hybrid cloud, the company says, allowing AI workloads to operate where the data resides—whether in data centers, across public clouds, or at the edge. This approach not only addresses data sovereignty, compliance, and operational integrity but also ensures consistent AI innovation across various environments.