Data, Corpora & Tokenization · 2009

The Unreasonable Effectiveness of Data

Alon Halevy, Peter Norvig, Fernando Pereira

Argued that for many hard problems, simple models trained on far more data outperform sophisticated models on less, shifting emphasis from clever algorithms to data scale.

Editorial record

Plain-language summary

Drawing on web-scale examples, the authors contend that unreasonably large corpora let comparatively simple methods succeed where elaborate ones with little data fail, and urge researchers to embrace data. Written years before deep learning’s dominance, it foreshadowed the data-centric logic later formalized by scaling laws. It is a conceptual ancestor of the scaling era.

Knowledge graph

Relationships

Antecedents

Source record

Provenance

Record ID
P-513
Record created
2026-07-13
Last reviewed
2026-07-14
Record version
2

Citation caveat: Citation metadata is approximate and marked unverified in the source dataset.