{
  "id": "bbg-p0366-platform-selection-and-tradeoffs-platform",
  "title": "RAG vs Fine-Tuning",
  "chapter": "ai-models-and-llm-systems",
  "batch": "15",
  "rank": 143,
  "sourcePage": 366,
  "sourcePointer": "p. 366",
  "status": "accepted",
  "reviewerStatus": "reviewed",
  "fidelityScore": 0.9,
  "canvas": {
    "width": 960,
    "height": 640
  },
  "fireworksTechGraph": {
    "style": "style-1-flat-icon",
    "diagramType": "comparison",
    "topologyNotes": [
      "source page render inspected",
      "extracted page text inspected",
      "source page render and extracted text inspected",
      "preserve core comparison: RAG fetches fresh external knowledge at runtime, fine-tuning updates model weights offline",
      "omit decorative icon layout and long explanatory prose",
      "retargeted from platform-selection to ai-models-and-llm-systems"
    ],
    "publicBoundary": [
      "original vector output",
      "no source pixels",
      "no source mark or long wording"
    ]
  },
  "callouts": [],
  "sourceReview": {
    "conceptAnchors": [
      "concept: RAG uses runtime retrieval",
      "concept: fine-tuning updates model weights offline",
      "concept: both adapt LLMs to new tasks",
      "concept: freshness versus specialization tradeoff"
    ],
    "labelSource": "curated",
    "semanticStatus": "reviewed"
  },
  "groups": [
    {
      "id": "rag",
      "label": "Retrieval-augmented generation",
      "x": 64,
      "y": 130,
      "w": 388,
      "h": 302
    },
    {
      "id": "fine",
      "label": "Fine-tuning",
      "x": 508,
      "y": 130,
      "w": 388,
      "h": 302
    }
  ],
  "shapes": [
    {
      "id": "query",
      "kind": "actor",
      "label": "Task",
      "detail": "question need",
      "x": 96,
      "y": 206,
      "w": 80,
      "h": 86,
      "tone": "blue"
    },
    {
      "id": "retrieve",
      "kind": "rect",
      "label": "Retrieve",
      "detail": "docs DB APIs",
      "x": 230,
      "y": 156,
      "w": 116,
      "h": 58,
      "tone": "green"
    },
    {
      "id": "ragModel",
      "kind": "hex",
      "label": "Base LLM",
      "detail": "grounded prompt",
      "x": 286,
      "y": 286,
      "w": 120,
      "h": 78,
      "tone": "purple"
    },
    {
      "id": "dataset",
      "kind": "rect",
      "label": "Training data",
      "detail": "domain examples",
      "x": 550,
      "y": 158,
      "w": 126,
      "h": 58,
      "tone": "orange"
    },
    {
      "id": "train",
      "kind": "rect",
      "label": "Offline training",
      "detail": "weight update",
      "x": 706,
      "y": 158,
      "w": 126,
      "h": 58,
      "tone": "red"
    },
    {
      "id": "fineModel",
      "kind": "hex",
      "label": "Tuned model",
      "detail": "specialized",
      "x": 646,
      "y": 286,
      "w": 126,
      "h": 78,
      "tone": "teal"
    },
    {
      "id": "fresh",
      "kind": "rect",
      "label": "Fresh knowledge",
      "detail": "runtime",
      "x": 124,
      "y": 346,
      "w": 126,
      "h": 58,
      "tone": "green"
    },
    {
      "id": "expert",
      "kind": "rect",
      "label": "Domain expert",
      "detail": "model behavior",
      "x": 786,
      "y": 346,
      "w": 126,
      "h": 58,
      "tone": "purple"
    }
  ],
  "connectors": [
    {
      "from": "query",
      "to": "retrieve",
      "label": "fetch",
      "flow": "main"
    },
    {
      "from": "retrieve",
      "to": "ragModel",
      "label": "augment",
      "flow": "data"
    },
    {
      "from": "ragModel",
      "to": "fresh",
      "label": "answer",
      "flow": "main"
    },
    {
      "from": "dataset",
      "to": "train",
      "label": "train",
      "flow": "control"
    },
    {
      "from": "train",
      "to": "fineModel",
      "label": "update",
      "flow": "data"
    },
    {
      "from": "fineModel",
      "to": "expert",
      "label": "serve",
      "flow": "main"
    }
  ]
}