{
  "title": "AI Compute Timeline",
  "description": "Training FLOPs milestones for AI history, from early electronic computing to frontier models. Observed, estimated, proxy, speculative, and projection rows are structurally separated.",
  "fields": {
    "year": "Year of milestone",
    "event": "Milestone or model/system name",
    "category": "Era or capability category",
    "value_numeric": "Numeric value plotted when applicable",
    "value_low": "Lower uncertainty bound when applicable",
    "value_high": "Upper uncertainty bound when applicable",
    "value_unit": "Unit for value_numeric, such as training FLOPs or ops/sec proxy",
    "estimate_status": "One of observed, estimated, proxy, speculative, projection",
    "source_id": "Source identifier for auditable rows",
    "confidence": "Qualitative confidence for the row",
    "display_label": "Short label used in chart annotations",
    "notes": "Audit notes and caveats"
  },
  "estimate_status_values": [
    "observed",
    "estimated",
    "proxy",
    "speculative",
    "projection"
  ],
  "sources": [
    {
      "id": "epoch",
      "name": "Epoch AI",
      "url": "https://epochai.org/",
      "accessed": "2026-01",
      "notes": "Primary source for training compute estimates"
    },
    {
      "id": "owid",
      "name": "Our World in Data",
      "url": "https://ourworldindata.org/artificial-intelligence",
      "accessed": "2026-01",
      "notes": "Historical AI milestones"
    },
    {
      "id": "kurzweil",
      "name": "Kurzweil (2005)",
      "url": "https://www.singularity.com/",
      "accessed": "2026-01",
      "notes": "Early compute and price-performance trend references"
    },
    {
      "id": "source_review_needed",
      "name": "Source review needed",
      "url": "https://github.com/mschwar/plots",
      "accessed": "2026-04",
      "notes": "Estimate or projection retained for chart continuity but flagged for source review"
    }
  ],
  "transformations": "Log10 values for y-axis. Ops/sec proxies and no-unit milestones are visually separated from training FLOPs. Speculative and projection rows are marker-coded and can be hidden in the Plotly chart.",
  "created": "2026-01",
  "last_updated": "2026-04-24",
  "author": "mschwar"
}