{
  "title": "Compute in the 2020 report",
  "report_year": 2020,
  "period": "Historical snapshot: October 2020. Dates and populations are specified per row.",
  "methodology": "The two figures describe different quantities: a model-specific cost estimate and a historical fixed-performance efficiency trend. Neither should be extrapolated as a universal rule or used as a current price.",
  "source_deck": "https://docs.google.com/presentation/d/1ZUimafgXCBSLsgbacd6-a-dqO7yLyzIl1ZJbiCBUUT4/edit?usp=sharing",
  "web_edition_date": "2026-10-11",
  "rows": [
    {
      "measure": "Estimated GPT-3 training cost",
      "value": "Approximately $10M",
      "definition": "Expert estimate cited in the report, not disclosed actual cost.",
      "printed_slide": null,
      "pdf_page": 17,
      "source_url": "https://www.stateof.ai/State-of-AI-Report-2020.pdf#page=17"
    },
    {
      "measure": "ImageNet compute-efficiency trend",
      "value": "Halving every 16 months",
      "definition": "Compute needed to reach a fixed performance level since 2012.",
      "printed_slide": null,
      "pdf_page": 22,
      "source_url": "https://www.stateof.ai/State-of-AI-Report-2020.pdf#page=22"
    }
  ]
}