{
  "kind": "all",
  "value": "all",
  "collectionKey": "slides:all:all:all-document-kinds:all-producers:all-orientations",
  "filters": {
    "documentKinds": [],
    "sourceTypes": [],
    "orientations": []
  },
  "total": 319975,
  "page": 906,
  "pageSize": 60,
  "pageCount": 5333,
  "rows": [
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "case_study",
      "function": "illustrate_case",
      "notes": "The slide uses three distinct charts to illustrate the 'spinout problem' (time, equity, and NPS).",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/68",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-68",
      "loopMatches": [
        {
          "to": 69,
          "from": 62,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-c1bcbf6f888c",
          "evidence": "Copilot, AI-first drug pipelines, CE-mark imaging, UK university spinouts, Stanford/Berkeley programmes.",
          "position": 11,
          "objective": "Inventory commercial AI applications: code, drug discovery, diagnostics, spinouts",
          "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": 80,
          "from": 5,
          "beatId": "019dd95a-0682-776c-8e35-2557e3799e96",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions, exec summary, Research and Industry sections inventory the state of AI.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "case_study",
      "function": "illustrate_case",
      "notes": "The slide uses a timeline-based case study to demonstrate the efficacy of a specific academic research funding model.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/69",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-69",
      "loopMatches": [
        {
          "to": 69,
          "from": 62,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-c1bcbf6f888c",
          "evidence": "Copilot, AI-first drug pipelines, CE-mark imaging, UK university spinouts, Stanford/Berkeley programmes.",
          "position": 11,
          "objective": "Inventory commercial AI applications: code, drug discovery, diagnostics, spinouts",
          "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": 80,
          "from": 5,
          "beatId": "019dd95a-0682-776c-8e35-2557e3799e96",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions, exec summary, Research and Industry sections inventory the state of AI.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "industry_trends",
      "function": "analyze_data",
      "notes": "Data source: dealroom.co. The slide uses stacked bar charts to show investment by round size.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/70",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-70",
      "loopMatches": [
        {
          "to": 80,
          "from": 70,
          "name": "Segmentation Split",
          "slug": "34-segmentation-split",
          "bestFor": "Customer analysis, market research, resource allocation",
          "matchId": "019dd95a-07fe-70ce-8d3d-c468bd4ac484",
          "evidence": "Eleven slides break the AI investment aggregate into round size, country, vertical, public vs private EV.",
          "position": 12,
          "objective": "Disaggregate AI VC investment by stage, geography, sector, public/private",
          "structure": "The Aggregate View -> Segment A Behavior -> Segment B Behavior -> The Insight in the Difference",
          "confidence": 80,
          "description": "Divide a whole into meaningful segments to reveal hidden patterns"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 80,
          "from": 5,
          "beatId": "019dd95a-0682-776c-8e35-2557e3799e96",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions, exec summary, Research and Industry sections inventory the state of AI.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "financial_analysis",
      "function": "analyze_data",
      "notes": "Data source: dealroom.co. The charts show a significant decline in large-scale funding compared to the relative stability of smaller rounds.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/71",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-71",
      "loopMatches": [
        {
          "to": 80,
          "from": 70,
          "name": "Segmentation Split",
          "slug": "34-segmentation-split",
          "bestFor": "Customer analysis, market research, resource allocation",
          "matchId": "019dd95a-07fe-70ce-8d3d-c468bd4ac484",
          "evidence": "Eleven slides break the AI investment aggregate into round size, country, vertical, public vs private EV.",
          "position": 12,
          "objective": "Disaggregate AI VC investment by stage, geography, sector, public/private",
          "structure": "The Aggregate View -> Segment A Behavior -> Segment B Behavior -> The Insight in the Difference",
          "confidence": 80,
          "description": "Divide a whole into meaningful segments to reveal hidden patterns"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 80,
          "from": 5,
          "beatId": "019dd95a-0682-776c-8e35-2557e3799e96",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions, exec summary, Research and Industry sections inventory the state of AI.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "comparison_table",
      "function": "compare_options",
      "notes": "The slide uses stacked bar charts to show EV by launch year cohorts.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/72",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-72",
      "loopMatches": [
        {
          "to": 80,
          "from": 70,
          "name": "Segmentation Split",
          "slug": "34-segmentation-split",
          "bestFor": "Customer analysis, market research, resource allocation",
          "matchId": "019dd95a-07fe-70ce-8d3d-c468bd4ac484",
          "evidence": "Eleven slides break the AI investment aggregate into round size, country, vertical, public vs private EV.",
          "position": 12,
          "objective": "Disaggregate AI VC investment by stage, geography, sector, public/private",
          "structure": "The Aggregate View -> Segment A Behavior -> Segment B Behavior -> The Insight in the Difference",
          "confidence": 80,
          "description": "Divide a whole into meaningful segments to reveal hidden patterns"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 80,
          "from": 5,
          "beatId": "019dd95a-0682-776c-8e35-2557e3799e96",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions, exec summary, Research and Industry sections inventory the state of AI.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "competitive_analysis",
      "function": "compare_peers",
      "notes": "The slide uses a bar-chart-in-table format to visualize the data.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/73",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-73",
      "loopMatches": [
        {
          "to": 80,
          "from": 70,
          "name": "Segmentation Split",
          "slug": "34-segmentation-split",
          "bestFor": "Customer analysis, market research, resource allocation",
          "matchId": "019dd95a-07fe-70ce-8d3d-c468bd4ac484",
          "evidence": "Eleven slides break the AI investment aggregate into round size, country, vertical, public vs private EV.",
          "position": 12,
          "objective": "Disaggregate AI VC investment by stage, geography, sector, public/private",
          "structure": "The Aggregate View -> Segment A Behavior -> Segment B Behavior -> The Insight in the Difference",
          "confidence": 80,
          "description": "Divide a whole into meaningful segments to reveal hidden patterns"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 80,
          "from": 5,
          "beatId": "019dd95a-0682-776c-8e35-2557e3799e96",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions, exec summary, Research and Industry sections inventory the state of AI.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "industry_trends",
      "function": "analyze_data",
      "notes": "Data source: dealroom.co. The chart shows a decline in absolute investment in 2022 YTD compared to 2021, but maintains a >50% share for the US.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/74",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-74",
      "loopMatches": [
        {
          "to": 80,
          "from": 70,
          "name": "Segmentation Split",
          "slug": "34-segmentation-split",
          "bestFor": "Customer analysis, market research, resource allocation",
          "matchId": "019dd95a-07fe-70ce-8d3d-c468bd4ac484",
          "evidence": "Eleven slides break the AI investment aggregate into round size, country, vertical, public vs private EV.",
          "position": 12,
          "objective": "Disaggregate AI VC investment by stage, geography, sector, public/private",
          "structure": "The Aggregate View -> Segment A Behavior -> Segment B Behavior -> The Insight in the Difference",
          "confidence": 80,
          "description": "Divide a whole into meaningful segments to reveal hidden patterns"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 80,
          "from": 5,
          "beatId": "019dd95a-0682-776c-8e35-2557e3799e96",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions, exec summary, Research and Industry sections inventory the state of AI.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "data_table",
      "function": "analyze_data",
      "notes": "The slide uses a combination of table and bar chart elements to visualize investment data across 24 industries.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/75",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-75",
      "loopMatches": [
        {
          "to": 80,
          "from": 70,
          "name": "Segmentation Split",
          "slug": "34-segmentation-split",
          "bestFor": "Customer analysis, market research, resource allocation",
          "matchId": "019dd95a-07fe-70ce-8d3d-c468bd4ac484",
          "evidence": "Eleven slides break the AI investment aggregate into round size, country, vertical, public vs private EV.",
          "position": 12,
          "objective": "Disaggregate AI VC investment by stage, geography, sector, public/private",
          "structure": "The Aggregate View -> Segment A Behavior -> Segment B Behavior -> The Insight in the Difference",
          "confidence": 80,
          "description": "Divide a whole into meaningful segments to reveal hidden patterns"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 80,
          "from": 5,
          "beatId": "019dd95a-0682-776c-8e35-2557e3799e96",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions, exec summary, Research and Industry sections inventory the state of AI.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "market_landscape",
      "function": "analyze_data",
      "notes": "Data source: dealroom.co. The chart shows a clear shift from public market exits to M&A activity in 2022.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/76",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-76",
      "loopMatches": [
        {
          "to": 80,
          "from": 70,
          "name": "Segmentation Split",
          "slug": "34-segmentation-split",
          "bestFor": "Customer analysis, market research, resource allocation",
          "matchId": "019dd95a-07fe-70ce-8d3d-c468bd4ac484",
          "evidence": "Eleven slides break the AI investment aggregate into round size, country, vertical, public vs private EV.",
          "position": 12,
          "objective": "Disaggregate AI VC investment by stage, geography, sector, public/private",
          "structure": "The Aggregate View -> Segment A Behavior -> Segment B Behavior -> The Insight in the Difference",
          "confidence": 80,
          "description": "Divide a whole into meaningful segments to reveal hidden patterns"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 80,
          "from": 5,
          "beatId": "019dd95a-0682-776c-8e35-2557e3799e96",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions, exec summary, Research and Industry sections inventory the state of AI.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "data_table",
      "function": "analyze_data",
      "notes": "Data source: dealroom.co. The chart shows a clear trend of increasing AI exits globally, with a specific focus on the performance of European regions versus the US.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/77",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-77",
      "loopMatches": [
        {
          "to": 80,
          "from": 70,
          "name": "Segmentation Split",
          "slug": "34-segmentation-split",
          "bestFor": "Customer analysis, market research, resource allocation",
          "matchId": "019dd95a-07fe-70ce-8d3d-c468bd4ac484",
          "evidence": "Eleven slides break the AI investment aggregate into round size, country, vertical, public vs private EV.",
          "position": 12,
          "objective": "Disaggregate AI VC investment by stage, geography, sector, public/private",
          "structure": "The Aggregate View -> Segment A Behavior -> Segment B Behavior -> The Insight in the Difference",
          "confidence": 80,
          "description": "Divide a whole into meaningful segments to reveal hidden patterns"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 80,
          "from": 5,
          "beatId": "019dd95a-0682-776c-8e35-2557e3799e96",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions, exec summary, Research and Industry sections inventory the state of AI.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "analyze_data",
      "notes": "The chart uses a stacked bar format to show funding rounds by size, with a projection for the full year 2022.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/78",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-78",
      "loopMatches": [
        {
          "to": 80,
          "from": 70,
          "name": "Segmentation Split",
          "slug": "34-segmentation-split",
          "bestFor": "Customer analysis, market research, resource allocation",
          "matchId": "019dd95a-07fe-70ce-8d3d-c468bd4ac484",
          "evidence": "Eleven slides break the AI investment aggregate into round size, country, vertical, public vs private EV.",
          "position": 12,
          "objective": "Disaggregate AI VC investment by stage, geography, sector, public/private",
          "structure": "The Aggregate View -> Segment A Behavior -> Segment B Behavior -> The Insight in the Difference",
          "confidence": 80,
          "description": "Divide a whole into meaningful segments to reveal hidden patterns"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 80,
          "from": 5,
          "beatId": "019dd95a-0682-776c-8e35-2557e3799e96",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions, exec summary, Research and Industry sections inventory the state of AI.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "analyze_data",
      "notes": "Data source: dealroom.co. The chart tracks EV by launch year cohorts.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/79",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-79",
      "loopMatches": [
        {
          "to": 80,
          "from": 70,
          "name": "Segmentation Split",
          "slug": "34-segmentation-split",
          "bestFor": "Customer analysis, market research, resource allocation",
          "matchId": "019dd95a-07fe-70ce-8d3d-c468bd4ac484",
          "evidence": "Eleven slides break the AI investment aggregate into round size, country, vertical, public vs private EV.",
          "position": 12,
          "objective": "Disaggregate AI VC investment by stage, geography, sector, public/private",
          "structure": "The Aggregate View -> Segment A Behavior -> Segment B Behavior -> The Insight in the Difference",
          "confidence": 80,
          "description": "Divide a whole into meaningful segments to reveal hidden patterns"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 80,
          "from": 5,
          "beatId": "019dd95a-0682-776c-8e35-2557e3799e96",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions, exec summary, Research and Industry sections inventory the state of AI.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "market_sizing",
      "function": "size_opportunity",
      "notes": "The slide uses a stacked bar chart to show EV growth by launch year cohorts and a grid of company logos with valuation details.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/80",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-80",
      "loopMatches": [
        {
          "to": 80,
          "from": 70,
          "name": "Segmentation Split",
          "slug": "34-segmentation-split",
          "bestFor": "Customer analysis, market research, resource allocation",
          "matchId": "019dd95a-07fe-70ce-8d3d-c468bd4ac484",
          "evidence": "Eleven slides break the AI investment aggregate into round size, country, vertical, public vs private EV.",
          "position": 12,
          "objective": "Disaggregate AI VC investment by stage, geography, sector, public/private",
          "structure": "The Aggregate View -> Segment A Behavior -> Segment B Behavior -> The Insight in the Difference",
          "confidence": 80,
          "description": "Divide a whole into meaningful segments to reveal hidden patterns"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 80,
          "from": 5,
          "beatId": "019dd95a-0682-776c-8e35-2557e3799e96",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Definitions, exec summary, Research and Industry sections inventory the state of AI.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "section_divider",
      "function": "transition",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/81",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-81",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "analyze_data",
      "notes": "The slide uses two scatter plots with trend lines to visualize the divergence in compute power and research output share.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/82",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-82",
      "loopMatches": [
        {
          "to": 85,
          "from": 82,
          "name": "Tale Two Worlds",
          "slug": "04-tale-two-worlds",
          "bestFor": "Competitive analysis, benchmarking, case for change",
          "matchId": "019dd95a-07fe-70ce-8d3d-cb4528ca80c2",
          "evidence": "Title 'compute chasm separating industry from academia', then academia hand-off to decentralized collectives and Stability AI.",
          "position": 13,
          "objective": "Show widening gap between industry and academia in large-model AI",
          "structure": "Current State -> Desired State / Benchmark -> The Gap & Implication",
          "confidence": 88,
          "description": "Show the gap between two states to drive urgency or highlight opportunity"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "timeline",
      "function": "establish_context",
      "notes": "The slide contrasts institutional bureaucracy with agile research collectives.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/83",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-83",
      "loopMatches": [
        {
          "to": 85,
          "from": 82,
          "name": "Tale Two Worlds",
          "slug": "04-tale-two-worlds",
          "bestFor": "Competitive analysis, benchmarking, case for change",
          "matchId": "019dd95a-07fe-70ce-8d3d-cb4528ca80c2",
          "evidence": "Title 'compute chasm separating industry from academia', then academia hand-off to decentralized collectives and Stability AI.",
          "position": 13,
          "objective": "Show widening gap between industry and academia in large-model AI",
          "structure": "Current State -> Desired State / Benchmark -> The Gap & Implication",
          "confidence": 88,
          "description": "Show the gap between two states to drive urgency or highlight opportunity"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "summarize",
      "notes": "The chart shows a clear decline in academic dominance (blue) and a rise in industry/collective collaborations (red/grey) in recent years.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/84",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-84",
      "loopMatches": [
        {
          "to": 85,
          "from": 82,
          "name": "Tale Two Worlds",
          "slug": "04-tale-two-worlds",
          "bestFor": "Competitive analysis, benchmarking, case for change",
          "matchId": "019dd95a-07fe-70ce-8d3d-cb4528ca80c2",
          "evidence": "Title 'compute chasm separating industry from academia', then academia hand-off to decentralized collectives and Stability AI.",
          "position": 13,
          "objective": "Show widening gap between industry and academia in large-model AI",
          "structure": "Current State -> Desired State / Benchmark -> The Gap & Implication",
          "confidence": 88,
          "description": "Show the gap between two states to drive urgency or highlight opportunity"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "present_solution",
      "notes": "The slide illustrates the ecosystem of Stability AI, showing how it supports various research groups (LAION, EleutherAI) and commercializes the output (DreamStudio).",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/85",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-85",
      "loopMatches": [
        {
          "to": 85,
          "from": 82,
          "name": "Tale Two Worlds",
          "slug": "04-tale-two-worlds",
          "bestFor": "Competitive analysis, benchmarking, case for change",
          "matchId": "019dd95a-07fe-70ce-8d3d-cb4528ca80c2",
          "evidence": "Title 'compute chasm separating industry from academia', then academia hand-off to decentralized collectives and Stability AI.",
          "position": 13,
          "objective": "Show widening gap between industry and academia in large-model AI",
          "structure": "Current State -> Desired State / Benchmark -> The Gap & Implication",
          "confidence": 88,
          "description": "Show the gap between two states to drive urgency or highlight opportunity"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "illustrate_case",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/86",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-86",
      "loopMatches": [
        {
          "to": 88,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-cdc5282c11c7",
          "evidence": "Defense product taxonomy, defense funding momentum, Ukraine GIS Arta example.",
          "position": 14,
          "objective": "Show AI being infused across defense product categories with evidence",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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 2022 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/87",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-87",
      "loopMatches": [
        {
          "to": 88,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-cdc5282c11c7",
          "evidence": "Defense product taxonomy, defense funding momentum, Ukraine GIS Arta example.",
          "position": 14,
          "objective": "Show AI being infused across defense product categories with evidence",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "case_study",
      "function": "illustrate_case",
      "notes": "The slide uses a process diagram to explain the 'Uber-like' dispatch model of the software.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/88",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-88",
      "loopMatches": [
        {
          "to": 88,
          "from": 86,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-cdc5282c11c7",
          "evidence": "Defense product taxonomy, defense funding momentum, Ukraine GIS Arta example.",
          "position": 14,
          "objective": "Show AI being infused across defense product categories with evidence",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "competitive_analysis",
      "function": "compare_peers",
      "notes": "Data source: CSET, stateof.ai 2022 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/89",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-89",
      "loopMatches": [
        {
          "to": 93,
          "from": 89,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-d067e6749c44",
          "evidence": "Reshoring fab data, CHIPS Act, US-China chip cutoff, EU AI Act progress.",
          "position": 15,
          "objective": "Survey geopolitical chip and regulation moves shaping the AI stack",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "analyze_data",
      "notes": "Includes a table summarizing the relative need for reshoring across different semiconductor device categories.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/90",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-90",
      "loopMatches": [
        {
          "to": 93,
          "from": 89,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-d067e6749c44",
          "evidence": "Reshoring fab data, CHIPS Act, US-China chip cutoff, EU AI Act progress.",
          "position": 15,
          "objective": "Survey geopolitical chip and regulation moves shaping the AI stack",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "situation_overview",
      "function": "establish_context",
      "notes": "Slide from the State of AI 2022 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/91",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-91",
      "loopMatches": [
        {
          "to": 93,
          "from": 89,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-d067e6749c44",
          "evidence": "Reshoring fab data, CHIPS Act, US-China chip cutoff, EU AI Act progress.",
          "position": 15,
          "objective": "Survey geopolitical chip and regulation moves shaping the AI stack",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "summarize",
      "notes": "Part of the 'State of AI 2022' report series.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/92",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-92",
      "loopMatches": [
        {
          "to": 93,
          "from": 89,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-d067e6749c44",
          "evidence": "Reshoring fab data, CHIPS Act, US-China chip cutoff, EU AI Act progress.",
          "position": 15,
          "objective": "Survey geopolitical chip and regulation moves shaping the AI stack",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "key_messages",
      "function": "summarize",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/93",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-93",
      "loopMatches": [
        {
          "to": 93,
          "from": 89,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-d067e6749c44",
          "evidence": "Reshoring fab data, CHIPS Act, US-China chip cutoff, EU AI Act progress.",
          "position": 15,
          "objective": "Survey geopolitical chip and regulation moves shaping the AI stack",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 93,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-35abf646aa8b",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Research, Industry, Politics sections accumulate signals.",
          "position": 2,
          "confidence": 55,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "section_divider",
      "function": "transition",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/94",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-94",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 106,
          "from": 94,
          "beatId": "019dd95a-0682-776c-8e35-381428a808af",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Climax",
          "beatSlug": "mountain-climax",
          "evidence": "Safety section confronts existential risk and alignment urgency.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "key_messages",
      "function": "establish_context",
      "notes": "Features quotes from Alan Turing, I.J. Good, and Marvin Minsky.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/95",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-95",
      "loopMatches": [
        {
          "to": 99,
          "from": 95,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-d51da57a5294",
          "evidence": "UK lead, 73% researchers concerned, 30x talent growth, $2B funding still trailing capabilities.",
          "position": 16,
          "objective": "Build the case that AI safety is becoming a serious, funded concern",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 106,
          "from": 94,
          "beatId": "019dd95a-0682-776c-8e35-381428a808af",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Climax",
          "beatSlug": "mountain-climax",
          "evidence": "Safety section confronts existential risk and alignment urgency.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "key_messages",
      "function": "cite_precedent",
      "notes": "Includes quotes from the UK National AI Strategy document.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/96",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-96",
      "loopMatches": [
        {
          "to": 99,
          "from": 95,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-d51da57a5294",
          "evidence": "UK lead, 73% researchers concerned, 30x talent growth, $2B funding still trailing capabilities.",
          "position": 16,
          "objective": "Build the case that AI safety is becoming a serious, funded concern",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 106,
          "from": 94,
          "beatId": "019dd95a-0682-776c-8e35-381428a808af",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Climax",
          "beatSlug": "mountain-climax",
          "evidence": "Safety section confronts existential risk and alignment urgency.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "key_takeaways",
      "function": "summarize",
      "notes": "The slide uses a series of diverging stacked bar charts to visualize survey agreement levels.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/97",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-97",
      "loopMatches": [
        {
          "to": 99,
          "from": 95,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-d51da57a5294",
          "evidence": "UK lead, 73% researchers concerned, 30x talent growth, $2B funding still trailing capabilities.",
          "position": 16,
          "objective": "Build the case that AI safety is becoming a serious, funded concern",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 106,
          "from": 94,
          "beatId": "019dd95a-0682-776c-8e35-381428a808af",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Climax",
          "beatSlug": "mountain-climax",
          "evidence": "Safety section confronts existential risk and alignment urgency.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "quantify_impact",
      "notes": "The chart uses a stacked bar to compare 2021 and 2022 researcher counts across different venues, highlighting a 30x gap between NeurIPS and Safety.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/98",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-98",
      "loopMatches": [
        {
          "to": 99,
          "from": 95,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-d51da57a5294",
          "evidence": "UK lead, 73% researchers concerned, 30x talent growth, $2B funding still trailing capabilities.",
          "position": 16,
          "objective": "Build the case that AI safety is becoming a serious, funded concern",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 106,
          "from": 94,
          "beatId": "019dd95a-0682-776c-8e35-381428a808af",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Climax",
          "beatSlug": "mountain-climax",
          "evidence": "Safety section confronts existential risk and alignment urgency.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "data_table",
      "function": "quantify_impact",
      "notes": "The slide uses two bar charts to contrast the scale of safety-focused funding (in millions) against general capabilities funding (in billions).",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/99",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-99",
      "loopMatches": [
        {
          "to": 99,
          "from": 95,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-d51da57a5294",
          "evidence": "UK lead, 73% researchers concerned, 30x talent growth, $2B funding still trailing capabilities.",
          "position": 16,
          "objective": "Build the case that AI safety is becoming a serious, funded concern",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 106,
          "from": 94,
          "beatId": "019dd95a-0682-776c-8e35-381428a808af",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Climax",
          "beatSlug": "mountain-climax",
          "evidence": "Safety section confronts existential risk and alignment urgency.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "present_solution",
      "notes": "Includes a chart showing Elo scores vs parameters and a chat example of a safety-aligned model.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/100",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-100",
      "loopMatches": [
        {
          "to": 106,
          "from": 100,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-db1f31ffae02",
          "evidence": "RLHF, red-teaming, mechanistic interpretability, goal misgeneralization, moral behavior, Conjecture lab.",
          "position": 17,
          "objective": "Catalogue alignment-research techniques and example labs",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 106,
          "from": 94,
          "beatId": "019dd95a-0682-776c-8e35-381428a808af",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Climax",
          "beatSlug": "mountain-climax",
          "evidence": "Safety section confronts existential risk and alignment urgency.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "diagnosis",
      "function": "present_framework",
      "notes": "Includes a process diagram for RLHF and a bar chart comparing model performance.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/101",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-101",
      "loopMatches": [
        {
          "to": 106,
          "from": 100,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-db1f31ffae02",
          "evidence": "RLHF, red-teaming, mechanistic interpretability, goal misgeneralization, moral behavior, Conjecture lab.",
          "position": 17,
          "objective": "Catalogue alignment-research techniques and example labs",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 106,
          "from": 94,
          "beatId": "019dd95a-0682-776c-8e35-381428a808af",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Climax",
          "beatSlug": "mountain-climax",
          "evidence": "Safety section confronts existential risk and alignment urgency.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "Includes a conceptual diagram of the red teaming process and a bar chart showing harmlessness by model size.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/102",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-102",
      "loopMatches": [
        {
          "to": 106,
          "from": 100,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-db1f31ffae02",
          "evidence": "RLHF, red-teaming, mechanistic interpretability, goal misgeneralization, moral behavior, Conjecture lab.",
          "position": 17,
          "objective": "Catalogue alignment-research techniques and example labs",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 106,
          "from": 94,
          "beatId": "019dd95a-0682-776c-8e35-381428a808af",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Climax",
          "beatSlug": "mountain-climax",
          "evidence": "Safety section confronts existential risk and alignment urgency.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "summarize",
      "notes": "The slide discusses the reverse-engineering of neural networks into human-interpretable programs.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/103",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-103",
      "loopMatches": [
        {
          "to": 106,
          "from": 100,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-db1f31ffae02",
          "evidence": "RLHF, red-teaming, mechanistic interpretability, goal misgeneralization, moral behavior, Conjecture lab.",
          "position": 17,
          "objective": "Catalogue alignment-research techniques and example labs",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 106,
          "from": 94,
          "beatId": "019dd95a-0682-776c-8e35-381428a808af",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Climax",
          "beatSlug": "mountain-climax",
          "evidence": "Safety section confronts existential risk and alignment urgency.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "diagnosis",
      "function": "diagnose",
      "notes": "The slide uses the CoinRun experiment to illustrate a specific AI safety failure mode.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/104",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-104",
      "loopMatches": [
        {
          "to": 106,
          "from": 100,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-db1f31ffae02",
          "evidence": "RLHF, red-teaming, mechanistic interpretability, goal misgeneralization, moral behavior, Conjecture lab.",
          "position": 17,
          "objective": "Catalogue alignment-research techniques and example labs",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 106,
          "from": 94,
          "beatId": "019dd95a-0682-776c-8e35-381428a808af",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Climax",
          "beatSlug": "mountain-climax",
          "evidence": "Safety section confronts existential risk and alignment urgency.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "case_study",
      "function": "illustrate_case",
      "notes": "The slide highlights the risk of AI being trained in environments that reward immoral behavior and proposes a solution to mitigate this.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/105",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-105",
      "loopMatches": [
        {
          "to": 106,
          "from": 100,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-db1f31ffae02",
          "evidence": "RLHF, red-teaming, mechanistic interpretability, goal misgeneralization, moral behavior, Conjecture lab.",
          "position": 17,
          "objective": "Catalogue alignment-research techniques and example labs",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 106,
          "from": 94,
          "beatId": "019dd95a-0682-776c-8e35-381428a808af",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Climax",
          "beatSlug": "mountain-climax",
          "evidence": "Safety section confronts existential risk and alignment urgency.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "client_example",
      "function": "illustrate_case",
      "notes": "Part of the State of AI 2022 report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/106",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-106",
      "loopMatches": [
        {
          "to": 106,
          "from": 100,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-db1f31ffae02",
          "evidence": "RLHF, red-teaming, mechanistic interpretability, goal misgeneralization, moral behavior, Conjecture lab.",
          "position": 17,
          "objective": "Catalogue alignment-research techniques and example labs",
          "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": 106,
          "from": 81,
          "beatId": "019dd95a-0682-776c-8e35-28fc5bded874",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": "triple-take-the-implications-so-what",
          "evidence": "Politics and Safety sections interpret what the facts mean for governance and risk.",
          "position": 2,
          "confidence": 78,
          "parentBeatName": "Reflection",
          "parentBeatSlug": "reflection"
        },
        {
          "to": 106,
          "from": 94,
          "beatId": "019dd95a-0682-776c-8e35-381428a808af",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Climax",
          "beatSlug": "mountain-climax",
          "evidence": "Safety section confronts existential risk and alignment urgency.",
          "position": 3,
          "confidence": 55,
          "parentBeatName": "Turn",
          "parentBeatSlug": "turn"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "section_divider",
      "function": "transition",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/107",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-107",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 109,
          "from": 107,
          "beatId": "019dd95a-0682-776c-8e35-2e04517cfad0",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Action (Now What)",
          "beatSlug": "triple-take-the-action-now-what",
          "evidence": "Section 5 'Predictions' issues 9 forward-looking calls for next 12 months.",
          "position": 3,
          "confidence": 78,
          "parentBeatName": "Resolution",
          "parentBeatSlug": "resolution"
        },
        {
          "to": 109,
          "from": 107,
          "beatId": "019dd95a-0682-776c-8e35-3f857f716df9",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Resolution",
          "beatSlug": "mountain-resolution",
          "evidence": "Predictions and thanks close the arc.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Resolution",
          "parentBeatSlug": "resolution"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "initiative_list",
      "function": "summarize",
      "notes": "The slide uses a numbered list format to present forward-looking statements.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/108",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-108",
      "loopMatches": [
        {
          "to": 108,
          "from": 108,
          "name": "Time Machine",
          "slug": "24-time-machine",
          "bestFor": "Vision casting, long-term strategy, investment pitches",
          "matchId": "019dd95a-07fe-70ce-8d3d-dc8d97fb8c73",
          "evidence": "Slide titled '9 predictions for the next 12 months' lists future events.",
          "position": 18,
          "objective": "Project 9 concrete predictions for the next 12 months",
          "structure": "Fast Forward to Success -> What Made It Possible -> Back to Today's Decision",
          "confidence": 88,
          "description": "Transport the audience to a future state where your solution has already succeeded"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 109,
          "from": 107,
          "beatId": "019dd95a-0682-776c-8e35-2e04517cfad0",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Action (Now What)",
          "beatSlug": "triple-take-the-action-now-what",
          "evidence": "Section 5 'Predictions' issues 9 forward-looking calls for next 12 months.",
          "position": 3,
          "confidence": 78,
          "parentBeatName": "Resolution",
          "parentBeatSlug": "resolution"
        },
        {
          "to": 109,
          "from": 107,
          "beatId": "019dd95a-0682-776c-8e35-3f857f716df9",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Resolution",
          "beatSlug": "mountain-resolution",
          "evidence": "Predictions and thanks close the arc.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Resolution",
          "parentBeatSlug": "resolution"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "closing_ask",
      "function": "summarize",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/109",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-109",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 109,
          "from": 107,
          "beatId": "019dd95a-0682-776c-8e35-2e04517cfad0",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Action (Now What)",
          "beatSlug": "triple-take-the-action-now-what",
          "evidence": "Section 5 'Predictions' issues 9 forward-looking calls for next 12 months.",
          "position": 3,
          "confidence": 78,
          "parentBeatName": "Resolution",
          "parentBeatSlug": "resolution"
        },
        {
          "to": 109,
          "from": 107,
          "beatId": "019dd95a-0682-776c-8e35-3f857f716df9",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Resolution",
          "beatSlug": "mountain-resolution",
          "evidence": "Predictions and thanks close the arc.",
          "position": 4,
          "confidence": 55,
          "parentBeatName": "Resolution",
          "parentBeatSlug": "resolution"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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",
      "function": "appendix",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/110",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-110",
      "loopMatches": [],
      "arcBeatMatches": [],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "appendix_disclosure",
      "function": "other",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/111",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-111",
      "loopMatches": [],
      "arcBeatMatches": [],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "team_bio",
      "function": "other",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/112",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-112",
      "loopMatches": [],
      "arcBeatMatches": [],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "team_bio",
      "function": "other",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/113",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-113",
      "loopMatches": [],
      "arcBeatMatches": [],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "docSlug": "cc8183ec02431b7a",
      "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
      "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": "cover",
      "function": "front_matter",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc/114",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-01cf0d8a8fbc#slide-114",
      "loopMatches": [],
      "arcBeatMatches": [],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
      "docSlug": "dd91c78f6570bf29",
      "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
      "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": 1,
      "slideType": "cover",
      "function": "front_matter",
      "notes": null,
      "imagePath": "https://imgproxy.kitesheet.com/l1AuJ9ypdAuuKEfHRlo118V-PiP4iAz0MXdo3Xz8r8M/rs:fit:1200:1200:0/q:82/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy9kZDkxYzc4ZjY1NzBiZjI5L3AwMDEuanBn",
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/1",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-1",
      "loopMatches": [],
      "arcBeatMatches": [],
      "imagePathAlt": "https://imgproxy.kitesheet.com/h_mcycmRiLDPQMd4ArPm5fSPlZc4MNIxQzLOzowtND0/rs:fit:1200:1200:0/q:82/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy9kZDkxYzc4ZjY1NzBiZjI5L3AwMDEucG5n",
      "thumbSrc": "https://imgproxy.kitesheet.com/HYuIuGdADU8E8sboaGNNh0WmE5FqenjbnhQL5rKIpC4/rs:fit:480:480:0/q:78/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy9kZDkxYzc4ZjY1NzBiZjI5L3AwMDEuanBn",
      "thumbSrcAlt": "https://imgproxy.kitesheet.com/rrhFg1X3gkTULUJTX2zA7Qk6-8ijZApWl5Hg9KumyEA/rs:fit:480:480:0/q:78/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy9kZDkxYzc4ZjY1NzBiZjI5L3AwMDEucG5n"
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
      "docSlug": "dd91c78f6570bf29",
      "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
      "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": 2,
      "slideType": "team_bio",
      "function": "front_matter",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/2",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-2",
      "loopMatches": [],
      "arcBeatMatches": [],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
      "docSlug": "dd91c78f6570bf29",
      "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
      "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": 3,
      "slideType": "team_bio",
      "function": "other",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/3",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-3",
      "loopMatches": [],
      "arcBeatMatches": [],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
      "docSlug": "dd91c78f6570bf29",
      "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
      "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": 4,
      "slideType": "agenda",
      "function": "front_matter",
      "notes": "The slide serves as a table of contents and mission statement for the report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/4",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-4",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 10,
          "from": 4,
          "beatId": "019dd95a-0682-776c-8e35-4dec34eefca8",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Setup & Stakes",
          "beatSlug": "mountain-setup-stakes",
          "evidence": "Definitions, agenda, exec summary set scope and prior-prediction stakes.",
          "position": 1,
          "confidence": 45,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
      "docSlug": "dd91c78f6570bf29",
      "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
      "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": 5,
      "slideType": "other",
      "function": "establish_context",
      "notes": "This slide serves as a foundational glossary for the report.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/5",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-5",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 10,
          "from": 4,
          "beatId": "019dd95a-0682-776c-8e35-4dec34eefca8",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Setup & Stakes",
          "beatSlug": "mountain-setup-stakes",
          "evidence": "Definitions, agenda, exec summary set scope and prior-prediction stakes.",
          "position": 1,
          "confidence": 45,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
      "docSlug": "dd91c78f6570bf29",
      "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
      "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": 6,
      "slideType": "other",
      "function": "establish_context",
      "notes": "This slide serves as a foundational reference for the rest of the deck.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/6",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-6",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 10,
          "from": 4,
          "beatId": "019dd95a-0682-776c-8e35-4dec34eefca8",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Setup & Stakes",
          "beatSlug": "mountain-setup-stakes",
          "evidence": "Definitions, agenda, exec summary set scope and prior-prediction stakes.",
          "position": 1,
          "confidence": 45,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
      "docSlug": "dd91c78f6570bf29",
      "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
      "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": 7,
      "slideType": "appendix",
      "function": "present_framework",
      "notes": "This slide acts as a key for interpreting model-related diagrams in subsequent slides.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/7",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-7",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 10,
          "from": 4,
          "beatId": "019dd95a-0682-776c-8e35-4dec34eefca8",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Setup & Stakes",
          "beatSlug": "mountain-setup-stakes",
          "evidence": "Definitions, agenda, exec summary set scope and prior-prediction stakes.",
          "position": 1,
          "confidence": 45,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
      "docSlug": "dd91c78f6570bf29",
      "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
      "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": 8,
      "slideType": "executive_summary",
      "function": "summarize",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/8",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-8",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 10,
          "from": 4,
          "beatId": "019dd95a-0682-776c-8e35-4dec34eefca8",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Setup & Stakes",
          "beatSlug": "mountain-setup-stakes",
          "evidence": "Definitions, agenda, exec summary set scope and prior-prediction stakes.",
          "position": 1,
          "confidence": 45,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
      "docSlug": "dd91c78f6570bf29",
      "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
      "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": 9,
      "slideType": "section_divider",
      "function": "transition",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/9",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-9",
      "loopMatches": [
        {
          "to": 10,
          "from": 9,
          "name": "Precedent",
          "slug": "09-precedent",
          "bestFor": "Risk mitigation, strategy validation, building confidence in new approaches",
          "matchId": "019dd95a-07fe-70ce-8d3d-e2991bb31991",
          "evidence": "Scorecard divider then a YES/NO/PARTIAL evidence table on 2022 predictions.",
          "position": 1,
          "objective": "Audit last year's predictions to earn analytical credibility",
          "structure": "The Precedent Case -> What Happened -> The Parallel -> Applied Learning",
          "confidence": 80,
          "description": "Use historical or external examples to validate your approach"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 10,
          "from": 4,
          "beatId": "019dd95a-0682-776c-8e35-4dec34eefca8",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Setup & Stakes",
          "beatSlug": "mountain-setup-stakes",
          "evidence": "Definitions, agenda, exec summary set scope and prior-prediction stakes.",
          "position": 1,
          "confidence": 45,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
      "docSlug": "dd91c78f6570bf29",
      "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
      "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": 10,
      "slideType": "comparison_table",
      "function": "summarize",
      "notes": "The slide uses a traffic light system (Green=YES, Red=NO, Amber=~) to indicate the status of predictions.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/10",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-10",
      "loopMatches": [
        {
          "to": 10,
          "from": 9,
          "name": "Precedent",
          "slug": "09-precedent",
          "bestFor": "Risk mitigation, strategy validation, building confidence in new approaches",
          "matchId": "019dd95a-07fe-70ce-8d3d-e2991bb31991",
          "evidence": "Scorecard divider then a YES/NO/PARTIAL evidence table on 2022 predictions.",
          "position": 1,
          "objective": "Audit last year's predictions to earn analytical credibility",
          "structure": "The Precedent Case -> What Happened -> The Parallel -> Applied Learning",
          "confidence": 80,
          "description": "Use historical or external examples to validate your approach"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 10,
          "from": 4,
          "beatId": "019dd95a-0682-776c-8e35-4dec34eefca8",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Setup & Stakes",
          "beatSlug": "mountain-setup-stakes",
          "evidence": "Definitions, agenda, exec summary set scope and prior-prediction stakes.",
          "position": 1,
          "confidence": 45,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
      "docSlug": "dd91c78f6570bf29",
      "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
      "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": 11,
      "slideType": "section_divider",
      "function": "transition",
      "notes": null,
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/11",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-11",
      "loopMatches": [],
      "arcBeatMatches": [
        {
          "to": 120,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-41afd44ef59f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Research + Industry sections inventory model, compute, funding facts.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 120,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-523bfb7f96e6",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Escalating capabilities, compute concentration and capital flows.",
          "position": 2,
          "confidence": 45,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
      "docSlug": "dd91c78f6570bf29",
      "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
      "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": 12,
      "slideType": "case_study",
      "function": "illustrate_case",
      "notes": "The chart shows a comparison of GPT-4, GPT-4 (no vision), and GPT-3.5 across various academic and professional exams.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/12",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-12",
      "loopMatches": [
        {
          "to": 21,
          "from": 12,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-e61d00ffc6e4",
          "evidence": "Sequential GPT-4, RLHF, LLaMa, popularity-mention slides converge on a single conclusion.",
          "position": 2,
          "objective": "Pile up evidence that GPT-4 and RLHF dominate the LLM landscape",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 82,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 120,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-41afd44ef59f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Research + Industry sections inventory model, compute, funding facts.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 120,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-523bfb7f96e6",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Escalating capabilities, compute concentration and capital flows.",
          "position": 2,
          "confidence": 45,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
      "docSlug": "dd91c78f6570bf29",
      "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
      "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": 13,
      "slideType": "industry_trends",
      "function": "present_framework",
      "notes": "Includes a process diagram illustrating the RLHF training pipeline.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/13",
      "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
      "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-13",
      "loopMatches": [
        {
          "to": 21,
          "from": 12,
          "name": "Pattern Hunter",
          "slug": "02-pattern-hunter",
          "bestFor": "Time-pressed audiences, building consensus, when data is strong",
          "matchId": "019dd95a-07fe-70ce-8d3d-e61d00ffc6e4",
          "evidence": "Sequential GPT-4, RLHF, LLaMa, popularity-mention slides converge on a single conclusion.",
          "position": 2,
          "objective": "Pile up evidence that GPT-4 and RLHF dominate the LLM landscape",
          "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
          "confidence": 82,
          "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 120,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-41afd44ef59f",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Facts (What)",
          "beatSlug": "triple-take-the-facts-what",
          "evidence": "Research + Industry sections inventory model, compute, funding facts.",
          "position": 1,
          "confidence": 78,
          "parentBeatName": "Setup",
          "parentBeatSlug": "setup"
        },
        {
          "to": 120,
          "from": 11,
          "beatId": "019dd95a-0682-776c-8e35-523bfb7f96e6",
          "arcName": "The Mountain",
          "arcSlug": "mountain",
          "beatName": "Rising Action",
          "beatSlug": "mountain-rising-action",
          "evidence": "Escalating capabilities, compute concentration and capital flows.",
          "position": 2,
          "confidence": 45,
          "parentBeatName": "Development",
          "parentBeatSlug": "development"
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    }
  ]
}