Scaling Laws & Compute · 2018
AI and Compute
Documented that the compute used in the largest AI training runs had grown roughly exponentially, quantifying the trend that later scaling laws and frontier models would ride.
Editorial record
Plain-language summary
The analysis charts training compute across landmark systems and finds a doubling time far faster than Moore’s law over the studied period. It made the compute-growth trend legible and widely cited as evidence that scaling, not just architecture, was driving progress. It is an early empirical anchor for the scaling narrative.
Knowledge graph
Relationships
Antecedents
Provides evidence forEvidence: Strongly supported
Scaling Laws for Neural Language Models
Documented the compute growth that scaling laws later formalized
book
Source record
Provenance
- Record ID
- P-514
- 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.