Discover how Red Hat Advanced Cluster Management for Kubernetes 2.16 offers intelligent, self-service operations to help you reclaim your nights and weekends. Learn about live migration of virtual machines, scaling infrastructure with freedom, ...
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Learn about training-time and post-training attacks on AI models, including data poisoning, backdoors, model theft, and privacy attacks. Discover how Red Hat's secure development lifecycle (SDLC) extends to AI and how to protect your models during .. ...
An important openSUSE kernel update resolves multiple security issues, enhancing system safety and performance.
Red Hat is pushing Kubernetes inference into the mainstream by contributing llm-d to the CNCF, as enterprises race to run AI models reliably and at scale.
Red Hat is contributing llm-d to the Cloud Native Computing Foundation (CNCF) as a Sandbox project to standardize high-performance, distributed AI inference serving within the cloud-native stack. This contribution aims to bridge the capabilities gap ...
As discussed in the first part of this blog, the SAS Viya analytical platform is not just a single application, but a suite of integrated applications.
NAIRR, a national program led by the NSF, is democratizing access to high-end AI compute for researchers by creating a shared national infrastructure. Red Hat provides an open source foundation, including OpenShift and OpenShift AI, to serve as the . ...
Moving AI from experimentation to enterprise reality requires a collaborative ecosystem of academia, startups, and open source communities built on transparent, hardware-agnostic standards. By "keeping the hood open," Red Hat aims to provide the ...
Explore the new risks and challenges of AI security, learn about potential attack vectors, and discover how to defend your AI systems with guardrails. This article is the first in a series on AI security.
Learn how to manage AI/ML data with version control using Red Hat OpenShift, Red Hat OpenShift AI, and lakeFS in this quickstart. Improve reproducibility, reduce errors, and scale your AI operations.