news
Red Hat and Fedora Leftovers
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Red Hat ☛ How to collaborate with Hey Hi (AI) to improve your Ansible skills
In January of 2023, I wrote an article about using an Hey Hi (AI) assistant to write Ansible Playbooks. At that time, I was not too impressed with the results. But I kept exploring AI, and I have to admit that now (February 2026) things look much better. The following is an article coached by me, but mostly written by Hey Hi (AI) and edited by a human.
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Red Hat ☛ Estimate GPU memory for LLM fine-tuning with Red Bait AI
Training Hub is an open source Python package that lets you fine-tune a pre-trained language model on a dataset of your choice, It is available as an open source package hosted on PyPI, and a downstream build is available on the Red Bait Python Index for use in Red Hat OpenShift AI workbenches as part of Red Hat Hey Hi (AI) 3.0. While language models are already powerful out of the box, fine-tuning a model on your dataset can improve its ability to handle specific tasks, making it more reliable for your business needs.
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Peter 'CzP' Czanik ☛ New toy: Installing Fedora GNU/Linux on the HP Z2 Mini
The data sheet of my new AI-focused mini workstation from HP does not mention Fedora, but I could install it just fine. I expected this though, because when I asked around about GNU/Linux support and hardware Hey Hi (AI) acceleration for AMD Ryzen 39X chips, all responses came from Fedora users… :-)
Installing Fedora on the HP Z2 Mini was a smooth experience, even though I hadn’t used the graphical installer for ages. I installed the Fedora server variant during Covid, and I’m upgrading it ever since. Still, using the graphical installer was easy, so Fedora was up and running in no time.
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Tim Waugh: Logsqueak: Rescuing Insights from the Logseq Journal
I’ve been using Logseq for a year now and it’s become the backbone of my workflow. I have pages dedicated to specific topics, concepts, projects, meetings… all sorts of things.
During my day, when I want to note something down or write something out to think about it, the daily Logseq journal is the obvious place for it to go. It has been an invaluable habit to build. But there’s a catch: the journal can easily become a black hole. It ends up as a chaotic mix of meeting notes, fleeting thoughts, random ideas, task lists and the occasional moment of genuine insight.
Most of the time, I try to link journal items to the relevant pages. Sometimes I remember to update those pages in light of new information. But other times I forget, and those insights get buried in the timeline, only resurfacing if I explicitly search for them.
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Red Hat Official ☛ Open data and the AI resilience premium
In 2026, the most forward-looking companies are starting to let go of the instinct to hold data tightly. Instead, they are focusing on what you might call a resilience advantage: working in open, collaborative networks that increase strength and flexibility instead of further isolation.
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Red Hat Official ☛ New observability features in Red Hat OpenShift 4.21 and Red Hat Advanced Cluster Management for Kubernetes 2.16
The cluster observability operator (COO) acts as a "meta-operator". Its primary job is to deploy and manage independent monitoring stacks that do not interfere with the core OpenShift metrics. In addition to this, the operator ships observability UI plugins and related advanced analytics features, including signal correlation (powered by Korrel8r) and incident detection for OpenShift. With the latest release, we announce the availability of two brand new features.