Everything a Senior Engineer Needs to Know About What's Inside an LLM

The shift from RNNs to transformers solved sequential bottlenecks and long-range decay issues with self-attention. Transformers use encoding, decoding, and tokenization to process sequences efficiently and accurately. This evolution led to models like GPT, which excel at tasks with minimal fine-tuning and universal objective functions.