Compute in the 2018 report
Evidence you can use
Compute in the 2018 report
Historical snapshot: June 2018. Dates and populations are specified per row.
| Measure | Reported value | Definition and source |
|---|---|---|
| Parallel-training hardware | 32 GPUs | Hardware count in the reported comparison with one GPU.2018 report, PDF page 11 |
| Reported training speedup | 25x | Speedup at the same accuracy in that comparison.2018 report, PDF page 11 |
| Cost-comparison target | 75.7% top-1 accuracy | ImageNet target used in the cloud-cost comparison.2018 report, PDF page 21 |
The speedup and cost examples concern specific training configurations. They do not establish a universal ranking of hardware or reflect present-day cloud prices.
Sources and dates
Historical snapshot published June 29, 2018. This web edition was prepared on 2026-10-11 from the online deck and original launch posts. Findings and forecasts retain their original time frame.
- 2018 report, PDF page 11Original 2018 report. This edition has no printed slide numbers. References use one-based PDF pages.
- 2018 report, PDF page 21Original 2018 report. This edition has no printed slide numbers. References use one-based PDF pages.
- 2018 report, PDF page 24Original 2018 report. This edition has no printed slide numbers. References use one-based PDF pages.
- State of AI Report 2018: online slides
- Stories from Air Street launch essayJuly 29, 2018.
Cite this page
Benaich, Nathan, and Ian Hogarth. “Compute in the 2018 report.” State of AI Report 2018. Historical report snapshot; web edition prepared 2026-10-11.