AI Tutorials

Learn what multi-head attention is, how self-attention works inside transformers, and why these mechanisms are essential for powering LLMs like GPT-5 and VLMs like CLIP, all with simple examples, diagrams, and code.

Learn how Vision Transformers (ViTs) leverage patch embeddings and self-attention to beat CNNs in modern image classification. This in-depth tutorial breaks down the ViT architecture, provides step-by-step Python code, and shows you when to choose ViTs for real-world computer-vision projects.

A step-by-step guide on fine-tuning the OpenAI GPT-OSS 20B model on the medical question and answer dataset for both accuracy and style adoption.

Learn how to use Runway Aleph to generate a video from start to finish, covering its capabilities and limitations through a practical example of creating a birthday video.

Learn how to set up, integrate, and run the Gemma 3 270M model in an Android application, along with best practices for ensuring its reliability and safety for on-device inference.

Learn how to build a Deep Research Assistant using Jan-v1's agentic reasoning capabilities, including local deployment, Streamlit app development, and more.

Learn about Kiro, an AI IDE, and its features, installation, and how it compares to other AI coding tools like Cursor.

Learn how to use OpenRouter's unified API to access various AI models, implement features like streaming, reasoning tokens, or structured outputs.

Learn how to build an interactive reasoning demo using MetaStone’s XBai o4 model, covering its reflective generative reasoning.

I tested Google's new Gemini 2.5 Deep Think mode on five real-world problems, ranging from PhD-level questions to business challenges.

Explore the latest OpenAI GPT-5 API features with code examples, including reasoning effort, verbosity control, chain-of-thought handoff, freeform input, output constraints, allowed tools, preambles, prompt optimization, and more.

Running GPT-OSS 120B locally, accessing it in a browser using the free chat applications, trying fast and free LLM inference providers, and exploring an LLM marketplace for the best and fastest model access.