Artificial intelligence training data supplies the patterns from which a model learns. Internet-scale text can teach broad language and recorded knowledge, while specialized scientific models may need curated structures, measurements, experiments or clinical observations.
A more capable model cannot infer every missing fact when the necessary evidence was never observed. Data quality, coverage, provenance and relevance limit what training can establish, especially for complex biological systems.
Acronyms and aliases
AI training data variantartificial intelligence training data variantmodel training data variant
Related terms
Frequently asked questions
Why is internet text insufficient for some scientific questions?
Text describes existing observations but cannot replace unperformed experiments or supply reliable measurements that were never collected from the biological system.
What makes scientific training data useful?
Useful data has clear provenance, reliable measurements, relevant conditions, sufficient coverage and documentation of bias, uncertainty and collection methods.
