Poolside's Titan training system operates inside its Model Factory, where routine recovery helps keep large training jobs running. The company describes checking hardware before a job starts, then applying error-specific recovery procedures when training stalls. A faulty node can be replaced and training restarted; failures that outlast automatic recovery trigger engineering alerts. The Titan article shows why operating a large training system involves more than fast computation: predictable failures need repeatable recovery, while unfamiliar problems still need diagnosis.
Terms in this piece · Glossary
pretraining — The first, biggest phase of building a model: training it on enormous amounts of text so it learns language, facts, and reasoning in general.
