transformer
2 articles
How Does an LLM Actually Run? From Tokens to the Next-Token Loop
A large language model looks like it is chatting, but underneath it is a mechanical pipeline: text becomes token IDs, IDs become vectors, position is injected, transformer blocks apply attention and feed-forward processing, residual streams keep the stack stable, and logits become the next token.
Stuffing a Computer Inside the Transformer: How This Trick Lets LLMs Crush Sudoku
Christos Tzamos highlights a fascinating gap: LLMs can solve research-grade math but still fumble basic arithmetic. His team's approach? Embed a computer directly inside the transformer — and it solves the hardest Sudoku puzzles at 100% accuracy.