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Sovereignty, Liquid Cooling, and the New Infrastructure Hierarchy with Gavin Dudley

The AI revolution is here, and data centers are its beating heart! Gone are the days of data centers being just overlooked IT infrastructure; they are now the "cool kids on the block," essential for powering the most significant technological shift of our generation.

5 UX Best Practices for Resilient & High-Performing Mobile Apps

What keeps users coming back to an app? Speed helps. Stability matters. But more than anything, people return to tools that feel easy to use, even under pressure. When an application responds clearly and behaves as expected, users are more likely to stick around. UX design plays a quiet but powerful role in this. It's not just about how something looks-it's how it works. The small details in navigation, layout, and screen flow all contribute to whether someone continues using an app or closes it within seconds.

3 Reasons Why You Should Use Custom Playwright Fixtures

In this video, Stefan Judis, Playwright ambassador, explains the power of Playwright fixtures while running tests in JavaScript or TypeScript. Learn how to streamline your test setup, remove repeated code, and leverage custom fixtures for cleaner and more efficient end-to-end tests. By the end of this video, you'll have a clear understanding of why you should use Playwright's native architecture to structure your testing project.

AI in Action with Kunal Kushwaha: 2 Demo Showcase. See What's Possible!

Join Kunal Kushwaha, Field CTO at Civo, for two demos using relaxAI. In the first demo, we'll show you how to deploy your own Large Language Model (LLM) inference engine using Ollama, giving you full control over your AI model. In the second demo, we'll demonstrate how to build custom AI integrations using relaxAI API, making it easy to add AI features to your existing applications. Whether you're an AI developer, MLOps team, or just curious about AI, this video is for you.

Hyperparameter tuning for LLMs using CircleCI matrix workflows

Hyperparameter tuning is a critical step in optimizing large language models (LLMs). Parameters such as learning rate, batch size, weight decay, and number of training epochs can significantly affect convergence behavior and final model performance. While several approaches like grid search or random search are widely used, executing them manually is inefficient; especially when each training run is compute-intensive.

From RPA to Agentic AI: Understanding the Shifting Landscape of Enterprise Automation

Over the past decade, organizations have embraced automation in waves – starting with basic task scripts and Robotic Process Automation (RPA), then moving to hyperautomation, and now exploring “agentic AI” as the next frontier. Each step in this evolution has expanded the scope of what can be automated, and revealed new challenges. This blog offers a detailed comparison of RPA, hyperautomation, and agentic AI, their key differences, strategic advantages, and potential drawbacks.