This episode explores the foundational stage of creating an LLM known as the pre-training phase. We break down the Trillion Token Diet by explaining how models move from random weights to sophisticated world models through the simple objective of next token prediction. You will learn about the Chinchilla Scaling Laws or the mathematical relationship between model size and data volume. We also discuss why the industry shifted from building bigger brains to better fed ones. By the end, you will understand the transition from raw statistical probability to parametric memory.
