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Densify

How to Optimize GPU

Nov 4, 2025 By Densify In Densify
The Problem: AI workloads are dynamic, unpredictable, and expensive. Data prep can choke your pipeline, training jobs hog GPUs without awareness, and inference, the most latency-sensitive phase, is notoriously hard to scale efficiently. Worse, traditional infrastructure tools treat GPU as a static commodity, ignoring model intent, workload shape, and sharing capabilities.
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Orbital Materials: WorldClass AI Models Built on CivoStack

Nov 4, 2025 By Civo In Civo
Daniel Miodovnik, COO of Orbital Materials, explains how the CivoStack enables world‑class AI models that outperform the big‑tech giants. He outlines the power‑draw and cooling of megawatt‑scale GPU racks, the water‑ and CO₂‑intensity of today’s data centres, and why a sovereign, Civo‑based solution is the key to speed, and predictable costs.
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Bridging the Gap Between AI Writing and Human Expression

Bridging the Gap Between AI Writing and Human Expression

Nov 4, 2025 By OpsMatters In OpsMatters
Never before has AI dominated the content we read every day as much as today. As each day passes, the online and offline worlds are being filled with AI writing, and soon, it will become difficult to find the human touch in any content. With AI being so prevalent, it has raised an important question: Will the human essence in writing just disappear as we let AI generate more and more writing each day? Does it really have to be an ongoing fight between human creativity and machine algorithms?
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redgate

Building dbRosetta Using AI: Part 1 of Many

Nov 3, 2025 By Grant Fritchey In Redgate
Like many of you, over the last couple of years, I’ve been using AI, or, well, let’s just name it appropriately, Large Language Models (LLM), as a part of my job. I’ve also used it in my hobby. With it, I’ve generated snippets of code, tested data conversions, even built a small database for a presentation. However, to date, I haven’t tried doing everything through the LLM. Now, I’m going to.
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digitate

AI Agent for Proactive Problem Management: A Shift Toward a Ticketless Future

Nov 3, 2025 By Sayali Pagrut In Digitate
As organizations rely on increasingly complex IT infrastructures, incident management often turns into a constant cycle of alerts, escalations, and fixes. While reactive responses may keep operations running, they rarely address the deeper systemic issues that slowly erode performance. Recurring incidents, silent failures, and hidden patterns are usually symptoms of unresolved root causes that traditional approaches struggle to uncover.
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cloudzero

AI And Sustainability: Measuring The Impact Of The Generative AI Boom

Nov 3, 2025 By Rachel Whitener In CloudZero
Before 2022, Alex Hanna worked on Google’s Ethical AI team. Today, she’s the director of research at the Distributed AI Research Institute, a transition sparked by Google’s handling of a paper exposing AI’s growing environmental footprint. So, how bad is it, really? That depends on who you ask. Take Jesse Dodge, a senior research analyst at the Allen Institute for AI. Jesse told NPR that a single ChatGPT query can use as much electricity as keeping a light bulb on for 20 minutes.
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Rovo AI: Create Work Items from Loom | Demo Den | Atlassian

Nov 3, 2025 By Atlassian In Atlassian
Ever wish you could turn a quick Loom recording into Jira work items without all the manual typing? Now you can! In this Demo Den episode, Pierre walks through a new Rovo AI feature that automatically converts your Loom videos into actionable Jira work items. Whether you're recording bug reports, feature requests, or project updates, Rovo handles the data entry for you. What Pierre covers: Turning Loom videos into work items with Rovo How it works in your AI-enabled Jira instance.
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Why AI Coding Assistants Fail (And How to Fix Them)

Nov 3, 2025 By GitKraken In GitKraken
Why do developers stop using AI coding assistants? According to Carnegie Mellon research, the top reason is unhelpful suggestions. Tabnine's Principal Architect John Feeney explains how context transforms AI coding tools from generic to genuinely useful. Learn the 4 Cs framework for maximizing AI assistant value: Context (workspace indexing), Connection (repo integration), Coaching (rules-based guidance), and Customization (fine-tuning). Discover how Retrieval Augmented Generation (RAG) helps AI understand your codebase, not just open source patterns.
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civo

The sovereignty of the builder: Lessons from Civo Navigate London 2025

Oct 31, 2025 By Emma Kinsey-Coates In Civo
Digital sovereignty isn’t won in policy papers. It’s earned in production. That was the challenge issued by Civo CEO Mark Boost and Board Director Kelsey Hightower at Civo Navigate London 2025. They argued that the cloud's real failure lies not with the providers, but with the customers who refused to change. Catch up on the full fireside chat below The power shift is underway, moving from large vendors back to the practitioner.
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harness

Streamline feature management with Harness MCP and Claude Code

Oct 31, 2025 By Austin Lai In Harness
Harness now supports the Model Context Protocol (MCP) for Feature Management and Experimentation (FME), enabling developers to interact with feature flags directly from AI-powered IDEs like Claude Code and Windsurf. The FME MCP tools make it easier to explore, understand, and manage feature flags through natural language, streamlining delivery and release workflows without leaving your development environment.
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