AI

In this test I’m comparing how different LLMs hosted on Ollama translate Hugo page in English to German.

This little Reranking Go code example is calling Ollama to generate embeddings for the query and for eache candidate document, then sorting descending by cosine similarity.

How PCIe Lanes Affect LLM Performance? Depending on the task. For training and multi-gpu inferrence - perdormance drop is significant.

In the Ollama models library there are models that able convert HTML content to Markdown, which is useful for content conversion tasks.

• Search is best for quick, straightforward information retrieval using keywords.
• Deep Search excels at understanding context and intent, delivering more relevant and comprehensive results for complex queries.

Will list here some AI-assisted coding tools and AI Coding Assistants and their nice sides.

Using LLMs is not very expensive, might be no need to buy new awesome GPU. Here is a list if LLM providers in the cloud with LLMs they host.

I’ve got a theory to test - if utilising ALL cores on Intel CPU would raise the speed of LLMs? This is bugging me that new gemma3 27 bit model (gemma3:27b, 17GB on ollama) is not fitting into 16GB VRAM of my GPU, and partially running on CPU.

In the midst of the modern world’s turmoil here I’m comparing tech specs of different cards suitable for AI tasks (Deep Learning, Object Detection and LLMs). They are all incredibly expensive though.

This guide explains how Ollama handles parallel requests (concurrency, queuing, and resource limits), and how to tune it using the OLLAMA_NUM_PARALLEL environment variable (and related knobs).

Vibe coding is an AI-driven programming approach where developers describe desired functionality in natural language and let AI tools generate the code automatically — with minimal direct writing.

I’ve used MMDetection (mmengine, mdet, mmcv) quite a bit, And now looks like it’s out of the game. It’s a pity. I liked it’s model zoo.

DeepSeek’s first-generation of reasoning models with comparable performance to OpenAI-o1, including six dense models distilled from DeepSeek-R1 based on Llama and Qwen.

This Ollama CLI cheatsheet focuses on the commands you use every day (ollama ls, ollama serve, ollama run, ollama ps, model management, and common workflows), with examples you can copy/paste.

Not long ago was released. Let’s catch up and test how Mistral Small performs comparing to other LLMs.

Reranking is a second step in Retrieval Augmented Generation (RAG) systems, right between Retrieving and Generating.