Articles
Feb 5, 2026
Transformer Architecture: A Visual & Interactive Guide 2
Token Embeddings 0:00 /0:05 1× The Problem Computers don't understand words — they understand numbers. But how do we convert "cat" into something a neural network can process? Naive approach: Assign each word a number (cat=1, dog=2, …) * Problem: This implies "cat" and "dog" are as different as "cat" and "quantum physics" * We lose all semantic meaning Better approach: Represent each word as a vector in high-dimensional space where: * Similar
Feb 3, 2026
Transformer Architecture: A Visual & Interactive Guide
Part 1: Token Embeddings The Video 0:00 /0:10 1× The Problem Computers don't understand words — they understand numbers. But how do we convert "cat" into something a neural network can process? Naive approach: Assign each word a number (cat=1, dog=2, …) * Problem: This implies "cat" and "dog" are as different as "cat" and "quantum physics" * We lose all semantic meaning Better approach: Represent each word as a vector in high-dimensional spa