{
  "title": "AI progress in the 2022 report",
  "report_year": 2022,
  "period": "Historical snapshot: October 2022. Dates and populations are specified per row.",
  "methodology": "Model specifications are not direct quality scores. The scaling finding applies to the studied training regime, while generative-image examples reflect the state of the field before ChatGPT’s public launch.",
  "source_deck": "https://docs.google.com/presentation/d/1WrkeJ9-CjuotTXoa4ZZlB3UPBXpxe4B3FMs9R9tn34I/edit?usp=sharing",
  "web_edition_date": "2026-10-11",
  "rows": [
    {
      "measure": "Chinchilla model size",
      "value": "70B parameters",
      "definition": "Model specification in the scaling-law discussion.",
      "printed_slide": 26,
      "pdf_page": 26,
      "source_url": "https://www.stateof.ai/State-of-AI-Report-2022.pdf#page=26"
    },
    {
      "measure": "Chinchilla training data",
      "value": "1.4T tokens",
      "definition": "Training token count reported for Chinchilla.",
      "printed_slide": 26,
      "pdf_page": 26,
      "source_url": "https://www.stateof.ai/State-of-AI-Report-2022.pdf#page=26"
    },
    {
      "measure": "Image-generation method",
      "value": "Diffusion",
      "definition": "Family of methods discussed for DALL-E 2, Imagen, and Stable Diffusion.",
      "printed_slide": 30,
      "pdf_page": 30,
      "source_url": "https://www.stateof.ai/State-of-AI-Report-2022.pdf#page=30"
    }
  ]
}