Articles & Tutorials
149 technical articles covering AI, Machine Learning, Cybersecurity, Data Science, and Programming. Practical guides, tutorials, and deep dives — written for developers.
31 articles · GPT
GGUF Explained: The Practical Model Format Behind Modern Local AI
GGUF (GPT-Generated Unified Format) is the standard file format for storing quantized large language models locally. It packages model weig…
What Is Numerical Precision?
Quantization reduces model size by using lower-precision numbers (4-bit instead of 32-bit). A 7B model shrinks from 28 GB (FP32) to 3.5 GB …
What Is LM Studio?
LM Studio is a desktop application that makes local AI as easy as downloading an app. Browse models visually, download with one click, chat…
What Is llama.cpp?
llama.cpp is a plain C/C++ inference engine that runs LLMs on CPU without any dependencies. It is the foundation behind most local AI tools…
What Is Local AI?
Local AI means running AI models on your own computer — no internet, no API costs, no data leaving your machine. You need at least 8GB RAM …
Why Fair Benchmarking Matters
Key Takeaway --> 🎯 Key Takeaway Fair benchmarking requires controlled conditions: same repository, same commit, same task, same configura…
The Four Stages
Key Takeaway --> 🎯 Key Takeaway AI coding tools evolved through four stages: autocomplete finishes your lines, chat answers questions, as…
The Complete Loop
Key Takeaway --> 🎯 Key Takeaway Function calling lets an LLM decide which external tool to use and what arguments to pass — but the appli…
Free-Form vs Structured Output
Key Takeaway --> 🎯 Key Takeaway LLMs produce free-form text by default. To build reliable applications, you need structured output: valid…
Why "Looks Good" Is Never Enough
Key Takeaway --> 🎯 Key Takeaway Evaluating a RAG system requires measuring retrieval quality, answer faithfulness, and system performance…
What Are Tokens?
Key Takeaway Every LLM interaction has a finite context window — a fixed budget of tokens for both input and output. More context is not au…
The Sequence Modeling Problem
Key Takeaway Transformers process all tokens simultaneously using self-attention — a mechanism that lets every token compute how much it sh…