{ "kind": "all", "value": "all", "collectionKey": "slides:all:all:all-document-kinds:all-producers:all-orientations", "filters": { "documentKinds": [], "sourceTypes": [], "orientations": [] }, "total": 319975, "page": 1800, "pageSize": 30, "pageCount": 10666, "rows": [ { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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 uses a dual-column timeline format to display chronological releases of datasets.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/103", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-103", "loopMatches": [ { "to": 106, "from": 93, "name": "Iceberg", "slug": "10-iceberg", "bestFor": "Consulting, complex problem solving, organizational change", "matchId": "019dd95a-07fe-70ce-8d3d-154d2d6f882c", "evidence": "Surface (legislation/permits) -> sketchy metrics -> capital consolidation -> root tech limits of supervised perception.", "position": 12, "objective": "Diagnose why self-driving progress is slower than headlines suggest", "structure": "The Symptom (Visible) -> The System (Hidden) -> The Root Cause", "confidence": 70, "description": "Reveal that the visible problem is merely a symptom of a deeper root cause" } ], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 104, "slideType": "industry_trends", "function": "present_framework", "notes": "The slide uses a process flow diagram combined with gauge charts to show the distribution of ML usage across the autonomous driving stack.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/104", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-104", "loopMatches": [ { "to": 106, "from": 93, "name": "Iceberg", "slug": "10-iceberg", "bestFor": "Consulting, complex problem solving, organizational change", "matchId": "019dd95a-07fe-70ce-8d3d-154d2d6f882c", "evidence": "Surface (legislation/permits) -> sketchy metrics -> capital consolidation -> root tech limits of supervised perception.", "position": 12, "objective": "Diagnose why self-driving progress is slower than headlines suggest", "structure": "The Symptom (Visible) -> The System (Hidden) -> The Root Cause", "confidence": 70, "description": "Reveal that the visible problem is merely a symptom of a deeper root cause" } ], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 105, "slideType": "industry_trends", "function": "summarize", "notes": "Includes logos of Lyft, Waymo, and Uber at the bottom.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/105", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-105", "loopMatches": [ { "to": 106, "from": 93, "name": "Iceberg", "slug": "10-iceberg", "bestFor": "Consulting, complex problem solving, organizational change", "matchId": "019dd95a-07fe-70ce-8d3d-154d2d6f882c", "evidence": "Surface (legislation/permits) -> sketchy metrics -> capital consolidation -> root tech limits of supervised perception.", "position": 12, "objective": "Diagnose why self-driving progress is slower than headlines suggest", "structure": "The Symptom (Visible) -> The System (Hidden) -> The Root Cause", "confidence": 70, "description": "Reveal that the visible problem is merely a symptom of a deeper root cause" } ], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 106, "slideType": "industry_trends", "function": "summarize", "notes": "Part of the 'state of ai 2020' report series.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/106", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-106", "loopMatches": [ { "to": 106, "from": 93, "name": "Iceberg", "slug": "10-iceberg", "bestFor": "Consulting, complex problem solving, organizational change", "matchId": "019dd95a-07fe-70ce-8d3d-154d2d6f882c", "evidence": "Surface (legislation/permits) -> sketchy metrics -> capital consolidation -> root tech limits of supervised perception.", "position": 12, "objective": "Diagnose why self-driving progress is slower than headlines suggest", "structure": "The Symptom (Visible) -> The System (Hidden) -> The Root Cause", "confidence": 70, "description": "Reveal that the visible problem is merely a symptom of a deeper root cause" } ], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 107, "slideType": "industry_trends", "function": "quantify_impact", "notes": "The slide highlights the rapid evolution of specialized AI hardware, specifically focusing on Graphcore's technological advancement.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/107", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-107", "loopMatches": [ { "to": 110, "from": 107, "name": "David Goliath", "slug": "16-david-goliath", "bestFor": "Startups, disruptive innovation, competitive displacement", "matchId": "019dd95a-07fe-70ce-8d3d-19b5d7018f7a", "evidence": "Slide 108 directly compares Graphcore M2000 vs NVIDIA DGX-A100 cost.", "position": 13, "objective": "Position Graphcore against NVIDIA/Google in AI compute", "structure": "The Giant's Weakness -> Our Slingshot (Unique Edge) -> The Topple", "confidence": 70, "description": "Frame your initiative as the nimble underdog taking on a slow, bloated incumbent" } ], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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": "comparison_table", "function": "compare_options", "notes": "The slide uses a visual comparison of hardware units to illustrate cost efficiency.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/108", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-108", "loopMatches": [ { "to": 110, "from": 107, "name": "David Goliath", "slug": "16-david-goliath", "bestFor": "Startups, disruptive innovation, competitive displacement", "matchId": "019dd95a-07fe-70ce-8d3d-19b5d7018f7a", "evidence": "Slide 108 directly compares Graphcore M2000 vs NVIDIA DGX-A100 cost.", "position": 13, "objective": "Position Graphcore against NVIDIA/Google in AI compute", "structure": "The Giant's Weakness -> Our Slingshot (Unique Edge) -> The Topple", "confidence": 70, "description": "Frame your initiative as the nimble underdog taking on a slow, bloated incumbent" } ], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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": "industry_trends", "function": "quantify_impact", "notes": "The chart shows performance gains for Mask R-CNN, SSD, ResNet-50, Transformer, and GNMT models.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/109", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-109", "loopMatches": [ { "to": 110, "from": 107, "name": "David Goliath", "slug": "16-david-goliath", "bestFor": "Startups, disruptive innovation, competitive displacement", "matchId": "019dd95a-07fe-70ce-8d3d-19b5d7018f7a", "evidence": "Slide 108 directly compares Graphcore M2000 vs NVIDIA DGX-A100 cost.", "position": 13, "objective": "Position Graphcore against NVIDIA/Google in AI compute", "structure": "The Giant's Weakness -> Our Slingshot (Unique Edge) -> The Topple", "confidence": 70, "description": "Frame your initiative as the nimble underdog taking on a slow, bloated incumbent" } ], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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": "industry_trends", "function": "quantify_impact", "notes": "The slide highlights the performance leap of the Ampere architecture.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/110", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-110", "loopMatches": [ { "to": 110, "from": 107, "name": "David Goliath", "slug": "16-david-goliath", "bestFor": "Startups, disruptive innovation, competitive displacement", "matchId": "019dd95a-07fe-70ce-8d3d-19b5d7018f7a", "evidence": "Slide 108 directly compares Graphcore M2000 vs NVIDIA DGX-A100 cost.", "position": 13, "objective": "Position Graphcore against NVIDIA/Google in AI compute", "structure": "The Giant's Weakness -> Our Slingshot (Unique Edge) -> The Topple", "confidence": 70, "description": "Frame your initiative as the nimble underdog taking on a slow, bloated incumbent" } ], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 111, "slideType": "industry_trends", "function": "summarize", "notes": "The slide uses a combination of a bar-line chart for GitHub project growth and a line chart for search trends.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/111", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-111", "loopMatches": [ { "to": 115, "from": 111, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-1e509d37e8ee", "evidence": "MLOps growth, enterprise survey on revenue/cost impact, RPA scale.", "position": 14, "objective": "Show enterprise shift from R&D to MLOps and adoption metrics", "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion", "confidence": 70, "description": "Group multiple pieces of evidence that together point to a pattern or conclusion" } ], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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": "industry_trends", "function": "summarize", "notes": "The slide lists 12 specific regulatory requirements for AI applications.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/112", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-112", "loopMatches": [ { "to": 115, "from": 111, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-1e509d37e8ee", "evidence": "MLOps growth, enterprise survey on revenue/cost impact, RPA scale.", "position": 14, "objective": "Show enterprise shift from R&D to MLOps and adoption metrics", "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion", "confidence": 70, "description": "Group multiple pieces of evidence that together point to a pattern or conclusion" } ], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 113, "slideType": "data_table", "function": "analyze_data", "notes": "The chart uses a diverging stacked bar format to compare two distinct metrics (cost decrease vs revenue increase) across the same set of business functions.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/113", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-113", "loopMatches": [ { "to": 115, "from": 111, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-1e509d37e8ee", "evidence": "MLOps growth, enterprise survey on revenue/cost impact, RPA scale.", "position": 14, "objective": "Show enterprise shift from R&D to MLOps and adoption metrics", "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion", "confidence": 70, "description": "Group multiple pieces of evidence that together point to a pattern or conclusion" } ], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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": "industry_trends", "function": "analyze_data", "notes": "The slide uses a bubble-heatmap style table to visualize AI adoption across different industry sectors.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/114", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-114", "loopMatches": [ { "to": 115, "from": 111, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-1e509d37e8ee", "evidence": "MLOps growth, enterprise survey on revenue/cost impact, RPA scale.", "position": 14, "objective": "Show enterprise shift from R&D to MLOps and adoption metrics", "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion", "confidence": 70, "description": "Group multiple pieces of evidence that together point to a pattern or conclusion" } ], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 115, "slideType": "industry_trends", "function": "quantify_impact", "notes": "The chart shows ARR growth from $1M in 2015 to $360M in 2019.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/115", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-115", "loopMatches": [ { "to": 115, "from": 111, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-1e509d37e8ee", "evidence": "MLOps growth, enterprise survey on revenue/cost impact, RPA scale.", "position": 14, "objective": "Show enterprise shift from R&D to MLOps and adoption metrics", "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion", "confidence": 70, "description": "Group multiple pieces of evidence that together point to a pattern or conclusion" } ], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 116, "slideType": "client_example", "function": "illustrate_case", "notes": "The slide highlights the practical application of deep learning in voice assistants, contrasting performance with legacy systems.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/116", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-116", "loopMatches": [ { "to": 128, "from": 116, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-2076d04ec9c2", "evidence": "Thirteen consecutive case studies: dialogue, claims, fraud, ESG, robots, NLP.", "position": 15, "objective": "Parade real-world AI deployments across verticals", "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": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 117, "slideType": "client_example", "function": "illustrate_case", "notes": "The slide highlights the value proposition of Tractable's AI in the insurance industry, specifically for auto claims.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/117", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-117", "loopMatches": [ { "to": 128, "from": 116, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-2076d04ec9c2", "evidence": "Thirteen consecutive case studies: dialogue, claims, fraud, ESG, robots, NLP.", "position": 15, "objective": "Parade real-world AI deployments across verticals", "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": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 118, "slideType": "industry_trends", "function": "present_solution", "notes": "The slide highlights a specific product capability (Tinyclues) within the context of industry trends in AI/ML automation.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/118", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-118", "loopMatches": [ { "to": 128, "from": 116, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-2076d04ec9c2", "evidence": "Thirteen consecutive case studies: dialogue, claims, fraud, ESG, robots, NLP.", "position": 15, "objective": "Parade real-world AI deployments across verticals", "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": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 119, "slideType": "industry_trends", "function": "quantify_impact", "notes": "The slide uses a radar chart to compare four companies across five ESG pillars, supported by a corresponding data table with conditional formatting.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/119", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-119", "loopMatches": [ { "to": 128, "from": 116, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-2076d04ec9c2", "evidence": "Thirteen consecutive case studies: dialogue, claims, fraud, ESG, robots, NLP.", "position": 15, "objective": "Parade real-world AI deployments across verticals", "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": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 120, "slideType": "industry_trends", "function": "illustrate_case", "notes": "The chart shows a sharp increase in COVID-19 related phishing emails compared to general phishing emails during early 2020.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/120", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-120", "loopMatches": [ { "to": 128, "from": 116, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-2076d04ec9c2", "evidence": "Thirteen consecutive case studies: dialogue, claims, fraud, ESG, robots, NLP.", "position": 15, "objective": "Parade real-world AI deployments across verticals", "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": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 121, "slideType": "client_example", "function": "illustrate_case", "notes": "The slide uses a visual callout technique to map specific document errors to their locations on an ID card.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/121", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-121", "loopMatches": [ { "to": 128, "from": 116, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-2076d04ec9c2", "evidence": "Thirteen consecutive case studies: dialogue, claims, fraud, ESG, robots, NLP.", "position": 15, "objective": "Parade real-world AI deployments across verticals", "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": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 122, "slideType": "case_study", "function": "illustrate_case", "notes": "The slide highlights the efficiency gains of AI over manual compliance processes, specifically in adverse media coverage.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/122", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-122", "loopMatches": [ { "to": 128, "from": 116, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-2076d04ec9c2", "evidence": "Thirteen consecutive case studies: dialogue, claims, fraud, ESG, robots, NLP.", "position": 15, "objective": "Parade real-world AI deployments across verticals", "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": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 123, "slideType": "case_study", "function": "illustrate_case", "notes": "The slide uses a bar chart to show time reduction and a precision-recall curve to show performance maintenance.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/123", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-123", "loopMatches": [ { "to": 128, "from": 116, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-2076d04ec9c2", "evidence": "Thirteen consecutive case studies: dialogue, claims, fraud, ESG, robots, NLP.", "position": 15, "objective": "Parade real-world AI deployments across verticals", "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": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "authorId": "AirStreetCapital", "authorName": "Air Street Capital", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "vc_research", "sourceTypeLabel": "VC research", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.777, "pageNumber": 124, "slideType": "client_example", "function": "illustrate_case", "notes": "The slide highlights the rapid adoption of open-source AI research into large-scale production environments.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/124", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-124", "loopMatches": [ { "to": 128, "from": 116, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-2076d04ec9c2", "evidence": "Thirteen consecutive case studies: dialogue, claims, fraud, ESG, robots, NLP.", "position": 15, "objective": "Parade real-world AI deployments across verticals", "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": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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": 125, "slideType": "client_example", "function": "illustrate_case", "notes": "Part of the 'Industry' section of the State of AI 2020 report.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/125", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-125", "loopMatches": [ { "to": 128, "from": 116, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-2076d04ec9c2", "evidence": "Thirteen consecutive case studies: dialogue, claims, fraud, ESG, robots, NLP.", "position": 15, "objective": "Parade real-world AI deployments across verticals", "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": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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": 126, "slideType": "client_example", "function": "illustrate_case", "notes": "The slide uses a process flow diagram to illustrate the transition from a 3D file to a finished part via automated CNC programming.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/126", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-126", "loopMatches": [ { "to": 128, "from": 116, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-2076d04ec9c2", "evidence": "Thirteen consecutive case studies: dialogue, claims, fraud, ESG, robots, NLP.", "position": 15, "objective": "Parade real-world AI deployments across verticals", "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": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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": 127, "slideType": "industry_trends", "function": "summarize", "notes": "The chart shows a clear upward trend in the usage of various transformer models over time.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/127", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-127", "loopMatches": [ { "to": 128, "from": 116, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-2076d04ec9c2", "evidence": "Thirteen consecutive case studies: dialogue, claims, fraud, ESG, robots, NLP.", "position": 15, "objective": "Parade real-world AI deployments across verticals", "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": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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": 128, "slideType": "industry_trends", "function": "illustrate_case", "notes": "The slide highlights adoption across six major industries with specific metrics on downloads and contributors.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/128", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-128", "loopMatches": [ { "to": 128, "from": 116, "name": "Pattern Hunter", "slug": "02-pattern-hunter", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "matchId": "019dd95a-07fe-70ce-8d3d-2076d04ec9c2", "evidence": "Thirteen consecutive case studies: dialogue, claims, fraud, ESG, robots, NLP.", "position": 15, "objective": "Parade real-world AI deployments across verticals", "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": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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": 129, "slideType": "industry_trends", "function": "analyze_data", "notes": "The chart uses a combination of bar and line graphs to represent capital raised and deal count respectively, with 2020 data being annualized.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/129", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-129", "loopMatches": [], "arcBeatMatches": [ { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-ed2a8f38a754", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Facts (What)", "beatSlug": "triple-take-the-facts-what", "evidence": "Research, Talent, Industry sections inventory what happened in AI in 2020.", "position": 1, "confidence": 60, "parentBeatName": "Setup", "parentBeatSlug": "setup" }, { "to": 129, "from": 10, "beatId": "019dd95a-0682-776c-8e34-fc384f439bba", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Rising Action", "beatSlug": "mountain-rising-action", "evidence": "Research, Talent and Industry sections build momentum of AI progress.", "position": 2, "confidence": 40, "parentBeatName": "Development", "parentBeatSlug": "development" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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": 130, "slideType": "section_divider", "function": "transition", "notes": null, "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/130", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-130", "loopMatches": [], "arcBeatMatches": [ { "to": 170, "from": 130, "beatId": "019dd95a-0682-776c-8e34-f2fc34acb214", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Implications (So What)", "beatSlug": "triple-take-the-implications-so-what", "evidence": "Politics section unpacks ethical, geopolitical and labor consequences.", "position": 2, "confidence": 60, "parentBeatName": "Reflection", "parentBeatSlug": "reflection" }, { "to": 170, "from": 130, "beatId": "019dd95a-0682-776c-8e35-01ef1d0aee03", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Climax", "beatSlug": "mountain-climax", "evidence": "Politics section dramatises facial recognition, military, US/China conflicts.", "position": 3, "confidence": 40, "parentBeatName": "Turn", "parentBeatSlug": "turn" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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": 131, "slideType": "industry_trends", "function": "establish_context", "notes": "The slide highlights academic and investigative work that brought AI ethics into the mainstream.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/131", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-131", "loopMatches": [ { "to": 140, "from": 131, "name": "Ripple Effect", "slug": "26-ripple-effect", "bestFor": "Change management, scaling initiatives, demonstrating broad value", "matchId": "019dd95a-07fe-70ce-8d3d-270e46b4c916", "evidence": "Risks -> wrongful arrests -> Facebook $650M -> Clearview -> UK ruling -> WA law -> China lawsuit.", "position": 16, "objective": "Trace ripple of facial recognition harms from arrests to lawsuits to legislation", "structure": "Individual Impact -> Team Impact -> Organizational Impact -> Market/Industry Impact", "confidence": 70, "description": "Show how impact spreads from individual to team to organization to market" } ], "arcBeatMatches": [ { "to": 170, "from": 130, "beatId": "019dd95a-0682-776c-8e34-f2fc34acb214", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Implications (So What)", "beatSlug": "triple-take-the-implications-so-what", "evidence": "Politics section unpacks ethical, geopolitical and labor consequences.", "position": 2, "confidence": 60, "parentBeatName": "Reflection", "parentBeatSlug": "reflection" }, { "to": 170, "from": 130, "beatId": "019dd95a-0682-776c-8e35-01ef1d0aee03", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Climax", "beatSlug": "mountain-climax", "evidence": "Politics section dramatises facial recognition, military, US/China conflicts.", "position": 3, "confidence": 40, "parentBeatName": "Turn", "parentBeatSlug": "turn" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }, { "docId": "019dd923-5e88-73ef-bd5c-f812573a947a", "docSlug": "eea7524c557036f4", "documentTitle": "2020 Air Street Capital The State of AI Report 2020", "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": 132, "slideType": "geographic_map", "function": "establish_context", "notes": "The slide uses a color-coded map to visualize the prevalence of facial recognition technology globally.", "imagePath": null, "matchCount": 1, "evidence": null, "slideHref": "/slides/019dd923-5e88-73ef-bd5c-f812573a947a/132", "deckHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5c-f812573a947a#slide-132", "loopMatches": [ { "to": 140, "from": 131, "name": "Ripple Effect", "slug": "26-ripple-effect", "bestFor": "Change management, scaling initiatives, demonstrating broad value", "matchId": "019dd95a-07fe-70ce-8d3d-270e46b4c916", "evidence": "Risks -> wrongful arrests -> Facebook $650M -> Clearview -> UK ruling -> WA law -> China lawsuit.", "position": 16, "objective": "Trace ripple of facial recognition harms from arrests to lawsuits to legislation", "structure": "Individual Impact -> Team Impact -> Organizational Impact -> Market/Industry Impact", "confidence": 70, "description": "Show how impact spreads from individual to team to organization to market" } ], "arcBeatMatches": [ { "to": 170, "from": 130, "beatId": "019dd95a-0682-776c-8e34-f2fc34acb214", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Implications (So What)", "beatSlug": "triple-take-the-implications-so-what", "evidence": "Politics section unpacks ethical, geopolitical and labor consequences.", "position": 2, "confidence": 60, "parentBeatName": "Reflection", "parentBeatSlug": "reflection" }, { "to": 170, "from": 130, "beatId": "019dd95a-0682-776c-8e35-01ef1d0aee03", "arcName": "The Mountain", "arcSlug": "mountain", "beatName": "Climax", "beatSlug": "mountain-climax", "evidence": "Politics section dramatises facial recognition, military, US/China conflicts.", "position": 3, "confidence": 40, "parentBeatName": "Turn", "parentBeatSlug": "turn" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true } ] }