LLM 101

Curated articles on LLM fundamentals

13 ArticlesUpdated regularly

Featured Articles

FeaturedLLM-concepts

BERT vs GPT: What's the Difference?

BERT and GPT are both transformer models, but they work very differently. Learn which architecture fits your use case.

LLM Temperature Explained: Why AI Gives Different Answers Each Time

Temperature controls how random or deterministic an LLM's responses are. Learn when to turn it up for creativity or down for consistency.

What is Tokenization in AI? How LLMs Read Your Text

Tokenization is the first step in how AI understands your text. Learn why LLMs chop words into pieces and how this affects everything from pricing to model behavior.

Why Do LLMs Hallucinate? Understanding AI Confabulation

LLM hallucinations are confidently stated falsehoods. Learn why they happen and how to minimize them in your AI applications.

What is Semantic Search? From Keywords to Meaning

Learn how semantic search uses embeddings and vectors to find information by meaning, not just keywords—explained for engineers who know SQL.

Amaya Birek

1/6/2026

8 min read

FeaturedModel Optimization

LLM Quantization Guide: FP32 vs Int8 vs GGUF

Why shrinking your model is like compressing a JPEG—and how to do it without lobotomizing your AI.

Amaya Birek

11/23/2025

12 min read

FeaturedAI Architecture

The Bedrock of Intelligence: From a Single Neuron to the Heart of an LLM

Peel back the layers of Large Language Models to understand the artificial neuron, the power of ReLU, and how these simple units power the massive Transformer architecture.

Amaya Birek

11/20/2025

8 min read

FeaturedTechnical Analysis

Transformer Architecture Explained (7B Parameters)

What does the '7B' on an LLM really mean? This article provides a rigorous breakdown of the Transformer architecture, showing exactly where those billions of parameters come from and how they directly impact VRAM, latency, cost, and concurrency in real-world deployments.

From Classifier to Creator: The Generative Leap

How a simple idea — “predict the next thing” — powers everything from ChatGPT to image generators.

Deep dive into LLM Inference Engine

We've explored the intricate architecture of the Transformer model—the billions of parameters that form its brain. But a brain, no matter how powerful, is useless without a nervous system and a life-support machine. That system, in the world of AI, is the inference engine.

What is a Neural Network?

Learn what a neural network is and how it works conceptually. No hard math, just logic.

AI Embeddings Explained: From Text to Vectors

Learn what embeddings are, how embedding models create them, how to store and query them efficiently, and what trade-offs to consider when scaling large RAG systems.

Understanding Context Windows in Large Language Models: A Beginner's Guide

Learn what context windows are, why they matter in Large Language Models, and how they affect tasks like chatbots, document analysis, and RAG pipelines.

Amaya Birek

8/22/2025

10 min read