Self-Hosting

The future of AI isn’t just about smarter models - it’s about smarter silicon. Specialized hardware for LLM inference is driving a revolution similar to Bitcoin mining’s shift to ASICs.

The web was originally designed as a decentralized network where anyone could publish and connect. Over time, corporate platforms consolidated control, creating walled gardens where users are products and content is locked in. The Indie Web movement aims to restore the original promise of the web: personal ownership, creative freedom, and genuine connection.

NVIDIA DGX Spark is real, on sale Oct 15, 2025, and targeted at CUDA developers needing local LLM work with an integrated NVIDIA AI stack. US MSRP $3,999; UK/DE/JP retail is higher due to VAT and channel. AUD/KRW public sticker prices are not yet widely posted.

The Gemini protocol represents a return to the fundamentals of internet communication-a lightweight, secure, and privacy-respecting alternative to the increasingly complex modern web.

This guide provides a comprehensive overview of available Go SDKs for Ollama and compares their feature sets.

Here is a comparison between Qwen3:30b and GPT-OSS:20b focusing on instruction following and performance parameters, specs and speed:

Here’s a quick info on Write.as / WriteFreely - how it fits into the fediverse, where to get managed hosting, what the usage trend looks like, and how to self-host (plus rough costings).

In this post, we’ll explore two ways to connect your Python application to Ollama: 1. Via HTTP REST API; 2. Via the official Ollama Python library.

Proxmox Virtual Environment (Proxmox VE) is an open-source, type-1 hypervisor and datacenter orchestration platform built on Debian.

Let’s compare prices for top-level consumer GPUs, that are suitable for LLMs in particular and AI in general. Specifically I’m looking at RTX-5080 and RTX-5090 prices. They have slightly dropped.

Ollama’s GPT-OSS models have recurring issues handling structured output, especially when used with frameworks like LangChain, OpenAI SDK, vllm, and others.

Large Language Models (LLMs) are powerful, but in production we rarely want free-form paragraphs. Instead, we want predictable data: attributes, facts, or structured objects you can feed into an app. That’s LLM Structured Output.

For KDE Plasma fans, two Linux distributions frequently come up in discussion: Kubuntu and KDE Neon. They may appear similar - both ship with KDE Plasma as the default desktop, both are based on Ubuntu, and both are friendly to newcomers.

Here I am comparing how much VRAM new version of Ollama allocating for the model vs previous Ollama version. The new version is worse.

This guide will walk you through the process of changing the static IP address on an Ubuntu Server.

Ollama has quickly become one of the most popular tools for running LLMs locally. Its simple CLI, and streamlined model management have made it a go-to option for developers who want to work with AI models outside the cloud. But as with many promising platforms, there are already signs of Enshittification: