{
  "kind": "all",
  "value": "all",
  "collectionKey": "slides:all:all:all-document-kinds:all-producers:all-orientations",
  "filters": {
    "documentKinds": [],
    "sourceTypes": [],
    "orientations": []
  },
  "total": 319975,
  "page": 895,
  "pageSize": 60,
  "pageCount": 5333,
  "rows": [
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 65,
      "slideType": "data_table",
      "function": "analyze_data",
      "notes": "The chart uses a 100% stacked bar format to compare salary growth trends by country.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/65",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-65",
      "loopMatches": [
        {
          "to": 67,
          "from": 65,
          "name": "Cost Of Inaction",
          "slug": "27-cost-of-inaction",
          "bestFor": "Urgent budget requests, compliance, risk mitigation",
          "matchId": "019dd95a-07fe-70ce-8d3c-689ec650b673",
          "evidence": "Salaries climb -> $300-500k base anecdotes -> $120M Google self-driving boss as tipping point.",
          "position": 10,
          "objective": "Quantify escalating talent compensation arms race",
          "structure": "The Status Quo -> The Hidden Costs Accumulating -> The Future State of Inaction -> The Tipping Point",
          "confidence": 70,
          "description": "Quantify what happens if the audience does nothing"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 69,
          "from": 4,
          "beatId": "019dd95a-0682-776c-8e34-ad4df4fe3ce7",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions then research breakthroughs (transfer learning, hardware, RL) and talent supply data.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 66,
      "slideType": "key_takeaways",
      "function": "cite_precedent",
      "notes": "The slide uses external media citations to validate the trend of rising AI talent costs.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/66",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-66",
      "loopMatches": [
        {
          "to": 67,
          "from": 65,
          "name": "Cost Of Inaction",
          "slug": "27-cost-of-inaction",
          "bestFor": "Urgent budget requests, compliance, risk mitigation",
          "matchId": "019dd95a-07fe-70ce-8d3c-689ec650b673",
          "evidence": "Salaries climb -> $300-500k base anecdotes -> $120M Google self-driving boss as tipping point.",
          "position": 10,
          "objective": "Quantify escalating talent compensation arms race",
          "structure": "The Status Quo -> The Hidden Costs Accumulating -> The Future State of Inaction -> The Tipping Point",
          "confidence": 70,
          "description": "Quantify what happens if the audience does nothing"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 69,
          "from": 4,
          "beatId": "019dd95a-0682-776c-8e34-ad4df4fe3ce7",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions then research breakthroughs (transfer learning, hardware, RL) and talent supply data.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 67,
      "slideType": "client_example",
      "function": "illustrate_case",
      "notes": "The slide uses screenshots of news articles to provide evidence of industry trends regarding talent compensation and litigation.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/67",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-67",
      "loopMatches": [
        {
          "to": 67,
          "from": 65,
          "name": "Cost Of Inaction",
          "slug": "27-cost-of-inaction",
          "bestFor": "Urgent budget requests, compliance, risk mitigation",
          "matchId": "019dd95a-07fe-70ce-8d3c-689ec650b673",
          "evidence": "Salaries climb -> $300-500k base anecdotes -> $120M Google self-driving boss as tipping point.",
          "position": 10,
          "objective": "Quantify escalating talent compensation arms race",
          "structure": "The Status Quo -> The Hidden Costs Accumulating -> The Future State of Inaction -> The Tipping Point",
          "confidence": 70,
          "description": "Quantify what happens if the audience does nothing"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 69,
          "from": 4,
          "beatId": "019dd95a-0682-776c-8e34-ad4df4fe3ce7",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions then research breakthroughs (transfer learning, hardware, RL) and talent supply data.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 68,
      "slideType": "key_takeaways",
      "function": "summarize",
      "notes": "Includes logos for WiML and Black in AI.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/68",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-68",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 69,
          "from": 4,
          "beatId": "019dd95a-0682-776c-8e34-ad4df4fe3ce7",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions then research breakthroughs (transfer learning, hardware, RL) and talent supply data.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 69,
      "slideType": "data_table",
      "function": "analyze_data",
      "notes": "The chart shows a slight upward trend in female attendance at the NIPS conference over three years.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/69",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-69",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 69,
          "from": 4,
          "beatId": "019dd95a-0682-776c-8e34-ad4df4fe3ce7",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions then research breakthroughs (transfer learning, hardware, RL) and talent supply data.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 70,
      "slideType": "section_divider",
      "function": "transition",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/70",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-70",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 71,
      "slideType": "industry_trends",
      "function": "analyze_data",
      "notes": "The chart on the left shows patent counts by company (Microsoft, Google, Amazon, Facebook, Apple). The chart on the right shows R&D spend by company, categorized by Tech vs Non-tech.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/71",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-71",
      "loopMatches": [
        {
          "to": 73,
          "from": 71,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-6ee015b0dd0a",
          "evidence": "Patent filings concentrated -> R&D spend leadership -> cloud APIs -> TensorFlow framework war.",
          "position": 11,
          "objective": "Show GAFAMBAT capture AI infrastructure layer",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 75,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 72,
      "slideType": "market_landscape",
      "function": "present_solution",
      "notes": "The slide uses a comparative structure to show the parity in AI service offerings across the three major cloud providers.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/72",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-72",
      "loopMatches": [
        {
          "to": 73,
          "from": 71,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-6ee015b0dd0a",
          "evidence": "Patent filings concentrated -> R&D spend leadership -> cloud APIs -> TensorFlow framework war.",
          "position": 11,
          "objective": "Show GAFAMBAT capture AI infrastructure layer",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 75,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 73,
      "slideType": "industry_trends",
      "function": "analyze_data",
      "notes": "The slide uses two distinct metrics (GitHub stars and research citations) to validate the thesis of TensorFlow's market leadership.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/73",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-73",
      "loopMatches": [
        {
          "to": 73,
          "from": 71,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-6ee015b0dd0a",
          "evidence": "Patent filings concentrated -> R&D spend leadership -> cloud APIs -> TensorFlow framework war.",
          "position": 11,
          "objective": "Show GAFAMBAT capture AI infrastructure layer",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 75,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 74,
      "slideType": "problem_statement",
      "function": "frame_problem",
      "notes": "Includes a process diagram illustrating the drug development lifecycle from preclinical to clinical studies.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/74",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-74",
      "loopMatches": [
        {
          "to": 80,
          "from": 74,
          "name": "Day In Life",
          "slug": "14-day-in-life",
          "bestFor": "Product demos, UX reviews, investor pitches focusing on pain points",
          "matchId": "019dd95a-07fe-70ce-8d3c-735f28c87032",
          "evidence": "Drug dev too slow ($2.6B) -> healthcare overburdened -> breast-cancer case study -> ML deployments and trials.",
          "position": 12,
          "objective": "Show pharma/healthcare struggle and AI intervention",
          "structure": "The User's Struggle -> The Intervention (Your Solution) -> The Resolved State",
          "confidence": 65,
          "description": "Humanize abstract data by walking through a single user's struggle and resolution"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 75,
      "slideType": "industry_trends",
      "function": "illustrate_case",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/75",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-75",
      "loopMatches": [
        {
          "to": 80,
          "from": 74,
          "name": "Day In Life",
          "slug": "14-day-in-life",
          "bestFor": "Product demos, UX reviews, investor pitches focusing on pain points",
          "matchId": "019dd95a-07fe-70ce-8d3c-735f28c87032",
          "evidence": "Drug dev too slow ($2.6B) -> healthcare overburdened -> breast-cancer case study -> ML deployments and trials.",
          "position": 12,
          "objective": "Show pharma/healthcare struggle and AI intervention",
          "structure": "The User's Struggle -> The Intervention (Your Solution) -> The Resolved State",
          "confidence": 65,
          "description": "Humanize abstract data by walking through a single user's struggle and resolution"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 76,
      "slideType": "industry_trends",
      "function": "establish_context",
      "notes": "The slide uses a line chart for longitudinal spending data and a stacked area chart for age-related health morbidity.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/76",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-76",
      "loopMatches": [
        {
          "to": 80,
          "from": 74,
          "name": "Day In Life",
          "slug": "14-day-in-life",
          "bestFor": "Product demos, UX reviews, investor pitches focusing on pain points",
          "matchId": "019dd95a-07fe-70ce-8d3c-735f28c87032",
          "evidence": "Drug dev too slow ($2.6B) -> healthcare overburdened -> breast-cancer case study -> ML deployments and trials.",
          "position": 12,
          "objective": "Show pharma/healthcare struggle and AI intervention",
          "structure": "The User's Struggle -> The Intervention (Your Solution) -> The Resolved State",
          "confidence": 65,
          "description": "Humanize abstract data by walking through a single user's struggle and resolution"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 77,
      "slideType": "case_study",
      "function": "illustrate_case",
      "notes": "The slide uses a case study approach to frame the problem statement for AI application in healthcare.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/77",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-77",
      "loopMatches": [
        {
          "to": 80,
          "from": 74,
          "name": "Day In Life",
          "slug": "14-day-in-life",
          "bestFor": "Product demos, UX reviews, investor pitches focusing on pain points",
          "matchId": "019dd95a-07fe-70ce-8d3c-735f28c87032",
          "evidence": "Drug dev too slow ($2.6B) -> healthcare overburdened -> breast-cancer case study -> ML deployments and trials.",
          "position": 12,
          "objective": "Show pharma/healthcare struggle and AI intervention",
          "structure": "The User's Struggle -> The Intervention (Your Solution) -> The Resolved State",
          "confidence": 65,
          "description": "Humanize abstract data by walking through a single user's struggle and resolution"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 78,
      "slideType": "industry_trends",
      "function": "illustrate_case",
      "notes": "The slide uses a list-based structure to categorize AI applications in healthcare, supported by company logos and a biological diagram.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/78",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-78",
      "loopMatches": [
        {
          "to": 80,
          "from": 74,
          "name": "Day In Life",
          "slug": "14-day-in-life",
          "bestFor": "Product demos, UX reviews, investor pitches focusing on pain points",
          "matchId": "019dd95a-07fe-70ce-8d3c-735f28c87032",
          "evidence": "Drug dev too slow ($2.6B) -> healthcare overburdened -> breast-cancer case study -> ML deployments and trials.",
          "position": 12,
          "objective": "Show pharma/healthcare struggle and AI intervention",
          "structure": "The User's Struggle -> The Intervention (Your Solution) -> The Resolved State",
          "confidence": 65,
          "description": "Humanize abstract data by walking through a single user's struggle and resolution"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 79,
      "slideType": "industry_trends",
      "function": "illustrate_case",
      "notes": "The slide shows a workflow for training and testing a deep learning model for tumor detection in pathology slides, alongside examples of medical imaging (OCT and MRI).",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/79",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-79",
      "loopMatches": [
        {
          "to": 80,
          "from": 74,
          "name": "Day In Life",
          "slug": "14-day-in-life",
          "bestFor": "Product demos, UX reviews, investor pitches focusing on pain points",
          "matchId": "019dd95a-07fe-70ce-8d3c-735f28c87032",
          "evidence": "Drug dev too slow ($2.6B) -> healthcare overburdened -> breast-cancer case study -> ML deployments and trials.",
          "position": 12,
          "objective": "Show pharma/healthcare struggle and AI intervention",
          "structure": "The User's Struggle -> The Intervention (Your Solution) -> The Resolved State",
          "confidence": 65,
          "description": "Humanize abstract data by walking through a single user's struggle and resolution"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 80,
      "slideType": "industry_trends",
      "function": "analyze_data",
      "notes": "The chart uses a horizontal bar layout where each bar is composed of company logos.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/80",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-80",
      "loopMatches": [
        {
          "to": 80,
          "from": 74,
          "name": "Day In Life",
          "slug": "14-day-in-life",
          "bestFor": "Product demos, UX reviews, investor pitches focusing on pain points",
          "matchId": "019dd95a-07fe-70ce-8d3c-735f28c87032",
          "evidence": "Drug dev too slow ($2.6B) -> healthcare overburdened -> breast-cancer case study -> ML deployments and trials.",
          "position": 12,
          "objective": "Show pharma/healthcare struggle and AI intervention",
          "structure": "The User's Struggle -> The Intervention (Your Solution) -> The Resolved State",
          "confidence": 65,
          "description": "Humanize abstract data by walking through a single user's struggle and resolution"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 81,
      "slideType": "industry_trends",
      "function": "illustrate_case",
      "notes": "Includes screenshots of SenseTime's surveillance software interface.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/81",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-81",
      "loopMatches": [
        {
          "to": 85,
          "from": 81,
          "name": "Zoom In",
          "slug": "06-zoom-in",
          "bestFor": "Technical deep-dives, case studies, detailed analysis",
          "matchId": "019dd95a-07fe-70ce-8d3c-7442641e422c",
          "evidence": "China surveillance -> Project Maven -> Cambridge Analytica -> privacy preservation tooling.",
          "position": 13,
          "objective": "Zoom into surveillance/privacy as the dark side of AI",
          "structure": "The Big Picture -> Key Area of Focus -> Specific Detail -> Implication",
          "confidence": 68,
          "description": "Start broad, then progressively focus on specific details that prove your point"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 82,
      "slideType": "industry_trends",
      "function": "illustrate_case",
      "notes": "The slide uses news snippets to illustrate the ethical tensions in AI development for defense.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/82",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-82",
      "loopMatches": [
        {
          "to": 85,
          "from": 81,
          "name": "Zoom In",
          "slug": "06-zoom-in",
          "bestFor": "Technical deep-dives, case studies, detailed analysis",
          "matchId": "019dd95a-07fe-70ce-8d3c-7442641e422c",
          "evidence": "China surveillance -> Project Maven -> Cambridge Analytica -> privacy preservation tooling.",
          "position": 13,
          "objective": "Zoom into surveillance/privacy as the dark side of AI",
          "structure": "The Big Picture -> Key Area of Focus -> Specific Detail -> Implication",
          "confidence": 68,
          "description": "Start broad, then progressively focus on specific details that prove your point"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 83,
      "slideType": "industry_trends",
      "function": "establish_context",
      "notes": "The slide uses a visual collage of data-related icons and text labels to illustrate the breadth of personal data collection.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/83",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-83",
      "loopMatches": [
        {
          "to": 85,
          "from": 81,
          "name": "Zoom In",
          "slug": "06-zoom-in",
          "bestFor": "Technical deep-dives, case studies, detailed analysis",
          "matchId": "019dd95a-07fe-70ce-8d3c-7442641e422c",
          "evidence": "China surveillance -> Project Maven -> Cambridge Analytica -> privacy preservation tooling.",
          "position": 13,
          "objective": "Zoom into surveillance/privacy as the dark side of AI",
          "structure": "The Big Picture -> Key Area of Focus -> Specific Detail -> Implication",
          "confidence": 68,
          "description": "Start broad, then progressively focus on specific details that prove your point"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 84,
      "slideType": "industry_trends",
      "function": "establish_context",
      "notes": "Includes a counter-style infographic for 2017 data breaches and a stacked bar chart showing consumer confidence in institutions.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/84",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-84",
      "loopMatches": [
        {
          "to": 85,
          "from": 81,
          "name": "Zoom In",
          "slug": "06-zoom-in",
          "bestFor": "Technical deep-dives, case studies, detailed analysis",
          "matchId": "019dd95a-07fe-70ce-8d3c-7442641e422c",
          "evidence": "China surveillance -> Project Maven -> Cambridge Analytica -> privacy preservation tooling.",
          "position": 13,
          "objective": "Zoom into surveillance/privacy as the dark side of AI",
          "structure": "The Big Picture -> Key Area of Focus -> Specific Detail -> Implication",
          "confidence": 68,
          "description": "Start broad, then progressively focus on specific details that prove your point"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 85,
      "slideType": "industry_trends",
      "function": "summarize",
      "notes": "Part of the State of AI 2018 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/85",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-85",
      "loopMatches": [
        {
          "to": 85,
          "from": 81,
          "name": "Zoom In",
          "slug": "06-zoom-in",
          "bestFor": "Technical deep-dives, case studies, detailed analysis",
          "matchId": "019dd95a-07fe-70ce-8d3c-7442641e422c",
          "evidence": "China surveillance -> Project Maven -> Cambridge Analytica -> privacy preservation tooling.",
          "position": 13,
          "objective": "Zoom into surveillance/privacy as the dark side of AI",
          "structure": "The Big Picture -> Key Area of Focus -> Specific Detail -> Implication",
          "confidence": 68,
          "description": "Start broad, then progressively focus on specific details that prove your point"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 86,
      "slideType": "industry_trends",
      "function": "establish_context",
      "notes": "Part of the state.ai 2018 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/86",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-86",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 87,
      "slideType": "industry_trends",
      "function": "summarize",
      "notes": "Part of the State of AI 2018 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/87",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-87",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 88,
      "slideType": "industry_trends",
      "function": "illustrate_case",
      "notes": "The slide showcases technical capabilities of satellite imagery providers (Planet, Orbital Insight, Descartes Labs) using RGB and NDVI analysis.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/88",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-88",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 89,
      "slideType": "industry_trends",
      "function": "diagnose",
      "notes": "Part of the 'state.ai 2018' report series.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/89",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-89",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 90,
      "slideType": "industry_trends",
      "function": "summarize",
      "notes": "Part of a larger report series; slide focuses on practical applications of ML in a specific industry vertical.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/90",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-90",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 91,
      "slideType": "industry_trends",
      "function": "diagnose",
      "notes": "The slide uses a 'Why now?' framing to explain the rapid adoption of robotics in logistics.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/91",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-91",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 92,
      "slideType": "industry_trends",
      "function": "present_solution",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/92",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-92",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 93,
      "slideType": "industry_trends",
      "function": "illustrate_case",
      "notes": "The slide showcases GreyOrange, RightHand Robotics, and 6 River Systems.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/93",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-93",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 94,
      "slideType": "industry_trends",
      "function": "analyze_data",
      "notes": "The slide uses two charts to explain the economic rationale for increased automation in blue-collar sectors.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/94",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-94",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 95,
      "slideType": "industry_trends",
      "function": "illustrate_case",
      "notes": "Part of a larger report series; uses a list-based structure to categorize industry applications.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/95",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-95",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 96,
      "slideType": "client_example",
      "function": "illustrate_case",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/96",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-96",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 97,
      "slideType": "industry_trends",
      "function": "frame_problem",
      "notes": "The slide uses a combination of a line chart showing the food production gap and a pie chart showing investment distribution.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/97",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-97",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 98,
      "slideType": "industry_trends",
      "function": "analyze_data",
      "notes": "Slide from state.ai 2018 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/98",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-98",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 99,
      "slideType": "industry_trends",
      "function": "summarize",
      "notes": "Part of the State of AI 2018 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/99",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-99",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 100,
      "slideType": "industry_trends",
      "function": "illustrate_case",
      "notes": "Includes company logos and photographic examples of agricultural robotics.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/100",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-100",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 101,
      "slideType": "problem_statement",
      "function": "frame_problem",
      "notes": "The slide uses a structured layout to present key statistics justifying the need for autonomous technology.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/101",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-101",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 102,
      "slideType": "industry_trends",
      "function": "illustrate_case",
      "notes": "Part of the 'state of AI 2018' report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/102",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-102",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 103,
      "slideType": "industry_trends",
      "function": "illustrate_case",
      "notes": "The slide uses a navigation bar at the top and a report identifier at the bottom right.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/103",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-103",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 104,
      "slideType": "industry_trends",
      "function": "analyze_data",
      "notes": "Part of the state.ai 2018 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/104",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-104",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 105,
      "slideType": "industry_trends",
      "function": "present_solution",
      "notes": "Part of a larger report series (state.ai 2018).",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/105",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-105",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 106,
      "slideType": "industry_trends",
      "function": "frame_problem",
      "notes": "The slide uses two charts to illustrate the inefficiency of current work patterns.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/106",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-106",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 107,
      "slideType": "industry_trends",
      "function": "present_framework",
      "notes": "The slide uses a list-based structure to categorize automation technologies.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/107",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-107",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 108,
      "slideType": "industry_trends",
      "function": "illustrate_case",
      "notes": "The slide uses a 'Why now?' and 'Where and how is ML being used effectively?' structure to frame the industry trend.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/108",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-108",
      "loopMatches": [
        {
          "to": 108,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7a42bb8ead28",
          "evidence": "Parallel mini case studies: satellite, cybersec, warehouses, blue collar, agriculture, autonomy, finance, enterprise, materials.",
          "position": 14,
          "objective": "Catalogue vertical AI deployment evidence",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 72,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 108,
          "from": 56,
          "beatId": "019dd95a-0682-776c-8e34-c00b5f60e426",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Deeper Layer",
          "beatSlug": "onion-deeper-layer",
          "evidence": "Talent and industry deployment across verticals.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 109,
      "slideType": "section_divider",
      "function": "transition",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/109",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-109",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 110,
      "slideType": "appendix_methodology",
      "function": "establish_context",
      "notes": "The slide provides context for subsequent data slides by defining the sample size and recruitment methods for Pew and Brookings surveys.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/110",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-110",
      "loopMatches": [
        {
          "to": 122,
          "from": 110,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7f99ebc2936f",
          "evidence": "Multiple Pew/Brookings stats: 77% awareness, 76% inequality, 41% optimism, 32% threat, US/China leadership.",
          "position": 15,
          "objective": "Aggregate survey data on public attitudes to AI/automation",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 80,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 111,
      "slideType": "industry_trends",
      "function": "analyze_data",
      "notes": "The chart is a diverging stacked bar chart showing likelihood of job replacement.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/111",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-111",
      "loopMatches": [
        {
          "to": 122,
          "from": 110,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7f99ebc2936f",
          "evidence": "Multiple Pew/Brookings stats: 77% awareness, 76% inequality, 41% optimism, 32% threat, US/China leadership.",
          "position": 15,
          "objective": "Aggregate survey data on public attitudes to AI/automation",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 80,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 112,
      "slideType": "data_table",
      "function": "analyze_data",
      "notes": "Data source: Pew Research Center. The chart compares two metrics: 'Lost a job' and 'Had pay or hours reduced' across 13 demographic categories.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/112",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-112",
      "loopMatches": [
        {
          "to": 122,
          "from": 110,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7f99ebc2936f",
          "evidence": "Multiple Pew/Brookings stats: 77% awareness, 76% inequality, 41% optimism, 32% threat, US/China leadership.",
          "position": 15,
          "objective": "Aggregate survey data on public attitudes to AI/automation",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 80,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 113,
      "slideType": "data_table",
      "function": "analyze_data",
      "notes": "Data source: Pew Research Center. The chart uses a diverging bar format to show binary sentiment (likely vs not likely).",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/113",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-113",
      "loopMatches": [
        {
          "to": 122,
          "from": 110,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7f99ebc2936f",
          "evidence": "Multiple Pew/Brookings stats: 77% awareness, 76% inequality, 41% optimism, 32% threat, US/China leadership.",
          "position": 15,
          "objective": "Aggregate survey data on public attitudes to AI/automation",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 80,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 114,
      "slideType": "data_table",
      "function": "analyze_data",
      "notes": "Data source: Pew Research Center. The chart shows a consistent trend where those impacted by automation hold stronger opinions or higher levels of concern/enthusiasm regarding the concept.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/114",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-114",
      "loopMatches": [
        {
          "to": 122,
          "from": 110,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7f99ebc2936f",
          "evidence": "Multiple Pew/Brookings stats: 77% awareness, 76% inequality, 41% optimism, 32% threat, US/China leadership.",
          "position": 15,
          "objective": "Aggregate survey data on public attitudes to AI/automation",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 80,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 115,
      "slideType": "industry_trends",
      "function": "analyze_data",
      "notes": "Source: Brookings Institute, State of AI 2018 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/115",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-115",
      "loopMatches": [
        {
          "to": 122,
          "from": 110,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7f99ebc2936f",
          "evidence": "Multiple Pew/Brookings stats: 77% awareness, 76% inequality, 41% optimism, 32% threat, US/China leadership.",
          "position": 15,
          "objective": "Aggregate survey data on public attitudes to AI/automation",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 80,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 116,
      "slideType": "data_table",
      "function": "analyze_data",
      "notes": "Source: Brookings Institute, State of AI 2018 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/116",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-116",
      "loopMatches": [
        {
          "to": 122,
          "from": 110,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7f99ebc2936f",
          "evidence": "Multiple Pew/Brookings stats: 77% awareness, 76% inequality, 41% optimism, 32% threat, US/China leadership.",
          "position": 15,
          "objective": "Aggregate survey data on public attitudes to AI/automation",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 80,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 117,
      "slideType": "data_table",
      "function": "analyze_data",
      "notes": "Source: Brookings Institute, State of AI 2018 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/117",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-117",
      "loopMatches": [
        {
          "to": 122,
          "from": 110,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7f99ebc2936f",
          "evidence": "Multiple Pew/Brookings stats: 77% awareness, 76% inequality, 41% optimism, 32% threat, US/China leadership.",
          "position": 15,
          "objective": "Aggregate survey data on public attitudes to AI/automation",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 80,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 118,
      "slideType": "data_table",
      "function": "analyze_data",
      "notes": "Data source: Brookings Institute. Part of the State of AI 2018 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/118",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-118",
      "loopMatches": [
        {
          "to": 122,
          "from": 110,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7f99ebc2936f",
          "evidence": "Multiple Pew/Brookings stats: 77% awareness, 76% inequality, 41% optimism, 32% threat, US/China leadership.",
          "position": 15,
          "objective": "Aggregate survey data on public attitudes to AI/automation",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 80,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 119,
      "slideType": "data_table",
      "function": "analyze_data",
      "notes": "Source: Brookings Institute, State of AI 2018 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/119",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-119",
      "loopMatches": [
        {
          "to": 122,
          "from": 110,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7f99ebc2936f",
          "evidence": "Multiple Pew/Brookings stats: 77% awareness, 76% inequality, 41% optimism, 32% threat, US/China leadership.",
          "position": 15,
          "objective": "Aggregate survey data on public attitudes to AI/automation",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 80,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 120,
      "slideType": "data_table",
      "function": "analyze_data",
      "notes": "Data source: Brookings Institute. Slide from state.ai 2018 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/120",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-120",
      "loopMatches": [
        {
          "to": 122,
          "from": 110,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7f99ebc2936f",
          "evidence": "Multiple Pew/Brookings stats: 77% awareness, 76% inequality, 41% optimism, 32% threat, US/China leadership.",
          "position": 15,
          "objective": "Aggregate survey data on public attitudes to AI/automation",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 80,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 121,
      "slideType": "data_table",
      "function": "analyze_data",
      "notes": "Data source: Brookings Institute. The chart shows a significant portion (35%) of respondents do not know or provided no answer.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/121",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-121",
      "loopMatches": [
        {
          "to": 122,
          "from": 110,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7f99ebc2936f",
          "evidence": "Multiple Pew/Brookings stats: 77% awareness, 76% inequality, 41% optimism, 32% threat, US/China leadership.",
          "position": 15,
          "objective": "Aggregate survey data on public attitudes to AI/automation",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 80,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 122,
      "slideType": "industry_trends",
      "function": "analyze_data",
      "notes": "Data source: Brookings Institute. Part of the State of AI 2018 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/122",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-122",
      "loopMatches": [
        {
          "to": 122,
          "from": 110,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-7f99ebc2936f",
          "evidence": "Multiple Pew/Brookings stats: 77% awareness, 76% inequality, 41% optimism, 32% threat, US/China leadership.",
          "position": 15,
          "objective": "Aggregate survey data on public attitudes to AI/automation",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 80,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 123,
      "slideType": "industry_trends",
      "function": "analyze_data",
      "notes": "The slide uses a single data point (4.1%) to contrast with the narrative of automation-driven unemployment.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/123",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-123",
      "loopMatches": [
        {
          "to": 129,
          "from": 123,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-823fbc64276b",
          "evidence": "Five+ contiguous data slides: routine jobs flat, wages lag, unemployment duration, productivity divergence, income volatility.",
          "position": 16,
          "objective": "Stack indicators of structural shift in US labor market",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 78,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5c-f341d4394195",
      "docSlug": "46f66c49fd159048",
      "documentTitle": "2018 Air Street Capital The State of AI Report 2018",
      "authorId": "AirStreetCapital",
      "authorName": "Air Street Capital",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "vc_research",
      "sourceTypeLabel": "VC research",
      "presentationDate": null,
      "orientation": "landscape",
      "aspectRatio": 1.777,
      "pageNumber": 124,
      "slideType": "industry_trends",
      "function": "analyze_data",
      "notes": "The chart highlights the stagnation of routine cognitive and manual jobs compared to the growth of non-routine cognitive roles.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f341d4394195/124",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f341d4394195#slide-124",
      "loopMatches": [
        {
          "to": 129,
          "from": 123,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3c-823fbc64276b",
          "evidence": "Five+ contiguous data slides: routine jobs flat, wages lag, unemployment duration, productivity divergence, income volatility.",
          "position": 16,
          "objective": "Stack indicators of structural shift in US labor market",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 78,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 150,
          "from": 70,
          "beatId": "019dd95a-0682-776c-8e34-b35a0f5ce04f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Industry applications and political/labor consequences across verticals and geographies.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 150,
          "from": 109,
          "beatId": "019dd95a-0682-776c-8e34-c5963b5d1d13",
          "arcName": "The Onion",
          "arcSlug": "onion",
          "beatName": "Core Insight",
          "beatSlug": "onion-core-insight",
          "evidence": "Politics: labor market, public attitudes, AI nationalism.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    }
  ]
}