{
  "docId": "019de06f-b8a3-7331-8935-2a15d6d59d93",
  "docSlug": "041e12e95b005675c8303cd029ca09ef",
  "documentTitle": "OpenAI | Product Presentation Deck | 64 slides",
  "authorId": "openai",
  "authorName": "OpenAI",
  "documentKindSlug": "conference-presentation",
  "documentKindLabel": "Conference presentation",
  "sourceTypeSlug": "investor_relations",
  "sourceTypeLabel": "Investor relations",
  "presentationDate": "2018-09-01 00:00:00",
  "orientation": "landscape",
  "aspectRatio": 1.7777778,
  "pageNumber": 46,
  "pageCount": 64,
  "prevPage": 45,
  "nextPage": 47,
  "slideType": "quote_slide",
  "function": "cite_precedent",
  "density": "dense",
  "nDataPoints": 0,
  "notes": "The slide uses a quote to frame a historical perspective on the limitations of deep learning.",
  "elementsJson": null,
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019de06f-b8a3-7331-8935-2a15d6d59d93/46",
  "deckHref": "/decks/019de06f-b8a3-7331-8935-2a15d6d59d93",
  "deckJsonHref": "/decks/019de06f-b8a3-7331-8935-2a15d6d59d93.json",
  "deckAnchorHref": "/decks/019de06f-b8a3-7331-8935-2a15d6d59d93#slide-46",
  "components": [
    {
      "bbox": {
        "h": 0.3,
        "w": 0.15,
        "x": 0.05,
        "y": 0.535
      },
      "kind": "image",
      "text": "Cover of Perceptrons book",
      "attrs": null,
      "subkind": "illustration",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "1f0edace-5ce1-46b7-b22e-f57f24fba797",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.15,
        "w": 0.3,
        "x": 0.05,
        "y": 0.2
      },
      "kind": "paragraph",
      "text": "Lessons from history of science\nFundamental limits of deep learning\nPractical limits on compute",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "019361e4-9f23-469d-8daf-aab856893c65",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.2,
        "w": 0.7,
        "x": 0.22,
        "y": 0.53
      },
      "kind": "quote",
      "text": "We have the impression that many people in the connectionist community do not understand that [back-propagation] is merely a particular way to compute a gradient and have assumed that back-propagation is a new learning scheme that somehow gets around the basic limitations of hill-climbing.",
      "attrs": null,
      "subkind": "pull-quote",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "e5f67497-ec51-4990-87b5-4e2032ea4e53",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.2,
        "x": 0.22,
        "y": 0.8
      },
      "kind": "source-note",
      "text": "— Minsky & Papert (1988)",
      "attrs": null,
      "subkind": null,
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "89e523b6-aff1-42d0-8226-edf28a27d649",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.4,
        "x": 0.05,
        "y": 0.25
      },
      "kind": "title",
      "text": "Lessons from history of AI",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "51142a6f-e968-4bad-a7bb-e9d01558e183",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [],
  "frameworks": [
    {
      "name": "authority-citation",
      "slug": null,
      "matchId": "ea033d9a-2548-448c-99ae-34917050cf97",
      "evidence": "Uses a quote from Minsky & Papert to establish historical precedent.",
      "confidence": 0.9
    }
  ],
  "arcBeats": [],
  "loops": [
    {
      "to": 49,
      "from": 40,
      "name": "Cost Of Inaction",
      "slug": "27-cost-of-inaction",
      "bestFor": "Urgent budget requests, compliance, risk mitigation",
      "matchId": "9610c943-c755-4d2d-84ab-fc123a8fbc41",
      "evidence": "The presentation discusses the lessons from history and the risks of underestimating AGI.",
      "position": 1,
      "objective": "The importance of taking AGI seriously",
      "structure": "The Status Quo -> The Hidden Costs Accumulating -> The Future State of Inaction -> The Tipping Point",
      "confidence": 0.6,
      "description": "Quantify what happens if the audience does nothing"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}