{
  "title": "AI progress in the 2018 report",
  "report_year": 2018,
  "period": "Historical snapshot: June 2018. Dates and populations are specified per row.",
  "methodology": "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.",
  "source_deck": "https://docs.google.com/presentation/d/e/2PACX-1vS_RSaVAQib2P8LtDxBJLCvdWlixK9WmxVhB9HUoNNsXdXR0Ts8Il1jB4967EiHGbxxLEYK1V540VRQ/pub",
  "web_edition_date": "2026-10-11",
  "rows": [
    {
      "measure": "Transfer-learning example",
      "value": "Skin-lesion classification",
      "definition": "Repurposing features from the InceptionV3 image-recognition network.",
      "printed_slide": null,
      "pdf_page": 8,
      "source_url": "https://www.stateof.ai/State-of-AI-Report-2018.pdf#page=8"
    },
    {
      "measure": "Robustness example",
      "value": "Adversarial image perturbations",
      "definition": "Illustrated failure mode of image classifiers; not a population-wide error rate.",
      "printed_slide": null,
      "pdf_page": 48,
      "source_url": "https://www.stateof.ai/State-of-AI-Report-2018.pdf#page=48"
    }
  ]
}