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          "description": "Explicit prescription of what the audience should do next.",
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          "bestFor": "Any narrative-driven persuasive deck whose job is to move the audience: keynotes, fundraising pitches, capital-allocation board asks, all-hands behaviour-change talks, conference talks meant to shift mental models. Use it before structuring; pair with Pyramid when the deck must also withstand line-by-line scrutiny.",
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        "evidence": "The slide presents a key idea about automating CNC machine programming.",
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        "whenToUse": "Any narrative-driven persuasive deck whose job is to move the audience: keynotes, fundraising pitches, capital-allocation board asks, all-hands behaviour-change talks, conference talks meant to shift mental models. Use it before structuring; pair with Pyramid when the deck must also withstand line-by-line scrutiny.",
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          "description": "Using specific sensory details instead of abstract terms",
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          "description": "Grouping audience by attitude toward your message: Champions, Neutrals, Skeptics",
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        "evidence": "5M pip installs / 2,500 models / 164 languages.",
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          "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration",
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        "evidence": "The slide presents a bar chart with a clear and simple design.",
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          "description": "Making abstract concepts concrete through familiar comparisons",
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        "evidence": "'Cambrian explosion' biological metaphor.",
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        "confidence": 70,
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          "canonId": "019dd9e1-4d71-77c5-a8d6-20a534104995",
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          "description": "Icon grids and pictograms standing in for text.",
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        "evidence": "The slide presents a grid of industry logos.",
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          "canonId": "019dd956-990d-7620-82b3-6dd286f34568",
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          "description": "People adapt behavior based on what others do - show adoption and testimonials",
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        "matchId": "f5499e89-9015-458a-9cc5-bc67867a57d9",
        "evidence": "The slide mentions the number of downloads and contributors.",
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        "confidence": 0.5,
        "extraction": {
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      {
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          "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.",
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          "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.",
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          "categoryName": "Slide",
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        "agents": [
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        "matchId": "019dd95a-0fd5-7148-8ed0-161823e24473",
        "evidence": "Title: AI funding remains strong despite COVID.",
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        "priority": "Core",
        "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.",
        "confidence": 80,
        "extraction": {
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        "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.",
        "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.",
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        "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex."
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          "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae",
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          "description": "Choosing the right chart type for your data and message",
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        "evidence": "The use of a bar chart and line chart to display funding data.",
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        "matchId": "019dd95a-0fd5-7148-8ed0-1899be92cca9",
        "evidence": "$25B+, 350+ deals.",
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        "confidence": 75,
        "extraction": {
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          "canonId": "019dd956-981b-74f9-9096-5c8df03dab5a",
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          "description": "Stories are remembered up to 22x better than facts alone",
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        "evidence": "The slide presents a narrative about funding trends.",
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        "confidence": 0.6,
        "extraction": {
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          "text": "Congratulations on making it to the end of the State of AI Report 2020! Thanks for reading. In this report, we set out to capture a snapshot of the exponential progress in the field of machine learning, with a focus on developments since last year's issue that was published on 26th June 2019. We believe that AI will be a force multiplier on technological progress in our world, and that wider understanding of the field is critical if we are to navigate such a huge transition. We set out to compile a snapshot of all the things that caught our attention in the last year across the range of AI research, talent, industry and the emerging politics of AI. We would appreciate any and all feedback on how we could improve this Report further, as well as contribution suggestions for next year's edition. Thanks again for reading!",
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