AI progress in the 2018 report
Evidence you can use
AI progress in the 2018 report
Historical snapshot: June 2018. Dates and populations are specified per row.
| Measure | Reported value | Definition and source |
|---|---|---|
| Transfer-learning example | Skin-lesion classification | Repurposing features from the InceptionV3 image-recognition network.2018 report, PDF page 8 |
| Robustness example | Adversarial image perturbations | Illustrated failure mode of image classifiers; not a population-wide error rate.2018 report, PDF page 48 |
These are research examples from 2018, not clinical recommendations or a measurement of general intelligence. Transfer performance depends on the relationship between the original and new tasks; adversarial examples illustrate vulnerabilities rather than normal-use error frequency.
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 8Original 2018 report. This edition has no printed slide numbers. References use one-based PDF pages.
- 2018 report, PDF page 37Original 2018 report. This edition has no printed slide numbers. References use one-based PDF pages.
- 2018 report, PDF page 48Original 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. “AI progress in the 2018 report.” State of AI Report 2018. Historical report snapshot; web edition prepared 2026-10-11.