Free Lesson
Birth of a Model: Pre-Training and GPU Clusters
60 min
Nov 3, 2026 1:30 PM
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What you'll learn
How next-token prediction scales up
See how to teach a model grammar, facts, and patterns.
Use scaling laws to trade off parameters, data, compute
Learn to reason about model size, dataset size, and compute budget before you spend a dollar on training.
Know what breaks when training at scale
Understand GPU/TPU parallelism, checkpoints, and common failures, and why a base model isn't a chatbot yet.
Why this topic matters
Every AI assistant you use starts as a base model trained to predict the next token. Understanding pre-training explains what LLMs know, why they hallucinate, and why frontier models cost hundreds of millions to build. If you make decisions about AI products, budgets, or vendors, this is the foundation. A base model knows a lot but doesn't know how to behave, and that gap drives everything that comes next.
