A detailed look into the process of building and training large language models (LLMs), from data acquisition to reinforcement learning, and their inherent capabilities and limitations.

An initiative to replicate OpenAI’s Deep Research by open-sourcing the agentic framework, aiming for accessible, customizable, and locally-run AI research tools.

Huawei’s Ascend 910C emerges as a viable alternative for AI inference, offering a path towards reduced reliance on Nvidia GPUs despite ongoing challenges.

Strategies for staying informed without succumbing to the overwhelming negativity and outrage often found online.

Explore the concept of outrage fatigue, its causes, and strategies for staying informed without succumbing to apathy and burnout.

Explore how to build a production-ready RAG AI agent using N8N and Supabase without writing any code.

Learn how to transition an AI agent prototype into a production-ready Python application using Pydantic AI and OpenRouter, enabling powerful and cost-effective AI solutions.

Explore the power of Agentic RAG, a strategy to overcome limitations of standard Retrieval Augmented Generation by enabling LLMs to intelligently explore knowledge bases.

Explore the potential of combining reasoning LLMs like DeepSeek R1 with faster, lightweight models for efficient and insightful agentic workflows.

Explore how to integrate Crawl4AI with N8N for efficient, no-code web scraping and building RAG knowledge bases.