news
Fedora, Flatpak, and IBM Red Hat's Annual Event Being About 90% About Slop and Selling Microsoft
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OSTechNix ☛ Fedora Plans AI-Focused Linux Desktop With Stable LTS Kernel
Fedora plans to launch an AI Developer Desktop with a stable LTS kernel and pre-configured Atomic images to make local AI tools easier to run.
This plan prioritizes privacy and local execution but has sparked intense community backlash.
The core tension isn't about AI itself. It's about kernel stability as a prerequisite for AI hardware support. By shifting to an LTS kernel, Fedora is prioritizing reliable NVIDIA driver operation over its long-standing philosophy of shipping the latest kernel.
Despite the controversy, Fedora plans to offer a "Fedora Remix" specifically to include NVIDIA's CUDA runtime, a pragmatic license workaround that acknowledges legal restrictions while pushing forward technically, even as volunteers resign over the direction.
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Jan-Lukas Else ☛ Some of my favorite Flatpak apps
My favorite of those package tools is Flatpak. With Flathub (think of it as an app store for Linux), there’s a huge selection of pre-packaged software available, most of it up-to-date and installed with a single command. Flatpak generally provides isolation and granular options to control the permissions of the apps. On my setup, I also tried to replace most of the preinstalled GNOME apps with the versions from Flatpak, to take advantage of bugfixes or new features that might not appear in the LTS repositories of Ubuntu.
In this post I want to share some nice tools on Flathub I discovered since switching back to Linux. Maybe you find some of them useful.
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Red Hat Official ☛ Stop managing the past and start building IT’s future [Ed: "modernize" as in what? Adopt buzzwords?]
To survive this shift, you’ll hear the phrase “just modernize” thrown out. That’s a loaded term, however - how are you supposed to address all existing investments? What if an application cannot be “modernized” or it isn't worth the expense?
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Red Hat Official ☛ AI’s next inflection point: Transforming agents into enterprise superusers [Ed: This year's Red Hat event is all about slop, which is embarrassing; it helps IBM sell hype for the stock market]
Many of us are being asked to launch new ambitious AI initiatives while simultaneously maintaining the legacy systems the business depends on. To bridge this gap, we do not just need more models. We need a framework to translate model intelligence into institutional action. We need skills - discrete, portable and open capabilities that bridge the gap between a prompt and a production result.
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Red Hat Official ☛ The three pillars of trust: The hardened OpenShift foundation
Imagine a regional public utility responsible for keeping the lights on for millions of homes, schools, and hospitals. In this environment, a security breach is a threat to the community's safety. If the grid goes dark because of a technical failure or an outside attack, the city would come to a halt. To address this kind of threat and to deliver on the core mission, the future architecture of Red Hat OpenShift is anchored in three core pillars: Integrity, isolation, and identity.
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Red Hat Official ☛ The path to zero trust: Bridging the gap between AI development and OpSec [Ed: More and more slop peddling, nothing about Linux.]
When sensitive data, such as patient medical records or proprietary AI model weights are actively loaded into the CPU, GPU, and memory for processing, it must be decrypted. In a traditional cloud environment, this leaves the data fully exposed to compromised hypervisors, malicious cloud administrators, memory dump attacks, and the cloud provider itself.
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Red Hat Official ☛ The MCP catalog is here: Discover, deploy, and connect on Red Hat OpenShift AI
Red Hat OpenShift AI 3.4, part of the Red Hat AI portfolio, takes a different approach. We're introducing the MCP catalog (now in developer preview): a curated catalog of MCP servers that you can discover, deploy, and manage directly on Red Hat OpenShift. It ships pre-loaded with MCP servers from Red Hat, our technology partners, and the open source community, and we are actively adding more. You can also “bring your own” MCP servers—the same lifecycle management and runtime connectivity that powers the catalog applies to any MCP server you deploy on your cluster.
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Red Hat Official ☛ Supercharging local AI development with RHEL on NVIDIA DGX Spark [Ed: IBM is "all-in" with this Ponzi scheme that makes a bubble waiting to implode]
To solve this problem, Red Hat in collaboration with NVIDIA is bringing enterprise-grade AI development directly to the developer’s desk. We are excited to announce the development preview of Red Hat Enterprise Linux 10 (RHEL 10) on NVIDIA DGX Spark.
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Red Hat Official ☛ Strengthening security and consistency in the cloud with Red Hat and HashiCorp
HashiCorp Vault integration for secrets management
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Red Hat Official ☛ Red Hat Device Edge now available to run on NVIDIA Jetson Orin [Ed: Helping NVIDIA, the circular financing (accounting fraud) company, sell more slop hype]
During the tech preview phase, we saw tremendous interest from customers wanting to extend AI capabilities to the far edge, whether they are leveraging AI for advanced robotics and autonomous drone applications, or running lightweight AI apps in industrial settings. Now, organizations can confidently move these critical workloads into production on a consistent, flexible, and security-focused platform that enables faster data delivery and drives new innovations at the edge.
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Red Hat Official ☛ Red Hat Desktop brings Kubernetes-aligned development to the desktop
At Red Hat, our view is that most developers should not need to manage containers or Kubernetes directly. The most effective approach is to focus on writing business logic and push code to production through a platform like Red Hat OpenShift, using capabilities such as Red Hat OpenShift Dev Spaces and the OpenShift application platform to handle the underlying complexity.
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Red Hat Official ☛ Red Hat AI Inference brings llm-d to any managed Kubernetes, starting with CoreWeave and Microsoft Azure [Ed: IBM Red Hat peddling slop and Microsoft at the same time!]
Today at Red Hat Summit, we are excited to announce that Red Hat AI Inference now runs on any managed Kubernetes service. This expansion enables organizations to leverage a consistent, open inference stack and Kubernetes-native operations wherever they already run their workloads. At launch, we are delivering validated deployment blueprints on 2 platforms: CoreWeave Kubernetes Service (CKS) and Azure Kubernetes Service (AKS).