{
  "docId": "019dd923-5e88-73ef-bd5c-c94988b4c44e",
  "docSlug": "144b47269c1f560e",
  "documentTitle": "2023 Accel Generation AI",
  "authorId": "Accel",
  "authorName": "Accel",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "vc_research",
  "sourceTypeLabel": "VC research",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.777,
  "pageNumber": 47,
  "pageCount": 54,
  "prevPage": 46,
  "nextPage": 48,
  "slideType": "market_landscape",
  "function": "present_framework",
  "density": "balanced",
  "nDataPoints": 0,
  "notes": "The slide uses a simple list-based segmentation to categorize the Gen AI tooling landscape.",
  "elementsJson": [
    "headline_text",
    "bullet_list",
    "logo_grid",
    "infographic"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5e88-73ef-bd5c-c94988b4c44e/47",
  "deckHref": "/decks/019dd923-5e88-73ef-bd5c-c94988b4c44e",
  "deckJsonHref": "/decks/019dd923-5e88-73ef-bd5c-c94988b4c44e.json",
  "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-c94988b4c44e#slide-47",
  "components": [
    {
      "bbox": null,
      "kind": "callout",
      "text": "With the explosion of Generative AI applications and use-cases, start-ups and enterprises alike are turning to Gen AI-specific tooling / infrastructure for LLMs.",
      "attrs": null,
      "subkind": null,
      "toolName": "Visual emphasis",
      "toolSlug": "visual-emphasis",
      "confidence": null,
      "componentId": "019dd952-41aa-7578-83d1-6368963cc038",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.6,
        "w": 0.43,
        "x": 0.53,
        "y": 0.24
      },
      "kind": "framework",
      "text": "MARKET SEGMENTATION: Monitoring & Observability, Developer Tools, Model Tuning, Compute & Interference, Foundational Models",
      "attrs": null,
      "subkind": "instance",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "5d69069d-c3be-4587-84d8-25b43409354c",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.15,
        "w": 0.45,
        "x": 0.04,
        "y": 0.72
      },
      "kind": "image",
      "text": "Weaviate, Scale, Hugging Face, Snorkel, LangChain, AssemblyAI",
      "attrs": null,
      "subkind": "logo-grid",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "e432ff9b-09a4-4066-9bef-08a0af90d03c",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.3,
        "w": 0.4,
        "x": 0.04,
        "y": 0.28
      },
      "kind": "list",
      "text": "With the explosion of Generative AI applications and use-cases, start-ups and enterprises alike are turning to Gen AI-specific tooling / infrastructure for LLMs. LLM developers are demanding new tools across the entire stack - from monitoring and observability to model tuning and databases. Open source becoming an integral part of emerging Generative AI tooling / infrastructure stack",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "beb99dc4-08eb-48dc-b249-e3367e4964ad",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.7,
        "x": 0.02,
        "y": 0.07
      },
      "kind": "title",
      "text": "Emergence of Gen AI-native tooling & infrastructure",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "f33af0d9-a887-4442-9de2-9a6403dfae51",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "Social Proof",
      "slug": "social-proof",
      "agent": "Storyteller",
      "layer": "block",
      "matchId": "019de0f3-92fd-73d5-b3eb-0c6168fdf4b3",
      "evidence": "Logo grid mapped to stack layers",
      "confidence": 75
    },
    {
      "name": "2x2 matrix",
      "slug": "matrix-2x2",
      "agent": null,
      "layer": "slide",
      "matchId": "60cf10d7-f4dd-4e05-a90b-ba1f8f26056d",
      "evidence": "Although not a traditional 2x2 matrix, the slide's use of a framework/instance with categories may be related to a matrix-like structure.",
      "confidence": 0.5
    },
    {
      "name": "Action Titles",
      "slug": "action-titles",
      "agent": "Architect",
      "layer": "slide",
      "matchId": "019de0f3-92ae-7179-8309-1fa346125773",
      "evidence": "Title 'Emergence of Gen AI-native tooling & infrastructure'",
      "confidence": 85
    },
    {
      "name": "Annotation",
      "slug": "annotation",
      "agent": "Designer",
      "layer": "slide",
      "matchId": "019de0f3-92d6-74da-95f2-5f924cb84425",
      "evidence": "Callout describes the explosion of Gen AI use-cases",
      "confidence": 75
    }
  ],
  "frameworks": [
    {
      "name": "Gen AI Infrastructure Stack",
      "slug": null,
      "matchId": "019de0f3-94af-748e-978c-ab8f7737542a",
      "evidence": "Vertical infographic segmenting Monitoring / Dev Tools / Tuning / Compute / Foundational Models.",
      "confidence": 65
    },
    {
      "name": "market-segmentation",
      "slug": null,
      "matchId": "6048fd7f-468d-4943-92be-c8c176469eeb",
      "evidence": "The slide explicitly labels the right-hand column as 'MARKET SEGMENTATION' and lists categories.",
      "confidence": 0.9
    }
  ],
  "arcBeats": [
    {
      "to": 50,
      "from": 43,
      "beatId": "019de0f3-8090-72d1-8582-afa98d059142",
      "arcName": "The Triple Take",
      "arcSlug": "triple-take",
      "beatName": "The Action (Now What)",
      "beatSlug": null,
      "evidence": "What's Next divider then six forward-looking Gen AI trends p.44-50.",
      "position": 3,
      "confidence": 88,
      "parentBeatName": null,
      "parentBeatSlug": null
    }
  ],
  "loops": [
    {
      "to": 50,
      "from": 44,
      "name": "Pattern Hunter",
      "slug": "02-pattern-hunter",
      "bestFor": "Time-pressed audiences, building consensus, when data is strong",
      "matchId": "019de0f3-821e-745b-8df2-70ceaa089c9d",
      "evidence": "Six trends preview (p44) then one slide per trend with data + logos (p45-50).",
      "position": 10,
      "objective": "Stack six forward-looking Gen AI trends as the path forward",
      "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"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}