How to read this finding
The code-availability figure describes the source’s paper population, not every AI project. Parameter count is a model specification, not a score for reasoning or reliability.
What changed in language AI in 2020?
Models such as GPT-3, T5, and BART made transformer-based systems useful across generation, summarization, translation, and code-related tasks.
Evidence you can use
AI progress in the 2020 report
Historical snapshot: October 2020. Dates and populations are specified per row.
| Measure | Reported value | Definition and source |
|---|---|---|
| GPT-3 model size | 175B parameters | Model size reported in the training-cost discussion.2020 report, PDF page 17 |
| Papers publishing code | 15% | Share in the report’s cited code-availability analysis.2020 report, PDF page 11 |
The code-availability figure describes the source’s paper population, not every AI project. Parameter count is a model specification, not a score for reasoning or reliability.
Sources and dates
Historical snapshot published October 1, 2020. 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.
- 2020 report, PDF page 11Original 2020 report. This edition has no printed slide numbers. References use one-based PDF pages.
- 2020 report, PDF page 17Original 2020 report. This edition has no printed slide numbers. References use one-based PDF pages.
- 2020 report, PDF page 24Original 2020 report. This edition has no printed slide numbers. References use one-based PDF pages.
- State of AI Report 2020: online slides
- Nathan Benaich’s launch essayOctober 1, 2020.
Cite this page
Benaich, Nathan, and Ian Hogarth. “What changed in language AI in 2020?” State of AI Report 2020. Historical report snapshot; web edition prepared 2026-10-11.