Practice · Established · Advanced
Pretraining
The initial, most expensive training phase where a model learns general structure from a very large unlabelled corpus.
What Pretraining is
Pretraining produces the base model: fluent and knowledgeable but not yet an obedient assistant.
How it works
Data is collected, filtered, de-duplicated and decontaminated, then streamed through the model with a next-token objective across thousands of accelerators for weeks. Checkpoints, loss curves and evaluation runs monitor progress.
Why it matters
Pretraining decides the ceiling of what later stages can achieve, and it is the barrier that keeps frontier model creation limited to well-funded labs.
Common uses
- →Building base models
- →Domain-specific continued pretraining
Strengths
- ✓Creates broadly reusable capability
Watch for
- ✓Extremely capital and energy intensive
- ✓Data provenance is hard to audit
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