DeepSeek-R1

Learn how to build a fully private, high-performance coding assistant using DeepSeek R1, Ollama, and VS Code. This guide covers environment setup, model optimization, and local RAG implementation for zero-cost AI development.

A comprehensive guide to local LLM execution on macOS using Microsoft Foundry Local, featuring performance benchmarks and a Python implementation guide.

DeepSeek recently updated its R1 technical report from 22 to 86 pages, revealing the intricate details of its multi-stage training pipeline, failed experiments, and the path to DeepSeek-V4.