--- title: "Dense Slides: 120k players in a week: Lessons from the first viral CLIP app: Joseph Nelson" category: "slides" video_id: "OimPoLxioYg" sourceLabels: ["Captured video frames", "Local OpenCV slide-region detection"] --- # Dense Slides: 120k players in a week: Lessons from the first viral CLIP app: Joseph Nelson ## Source Video [120k players in a week: Lessons from the first viral CLIP app: Joseph Nelson](https://www.youtube.com/watch?v=OimPoLxioYg) ## Method This deck is slide-only. The existing captured video frame set supplies candidate frames, then local OpenCV rejects sponsor/title/speaker-only frames, crops visible slide surfaces, deduplicates, and saves the cropped slide images. ## Cropped Visible Slides ![[assets/dense-slides/OimPoLxioYg/slide-001.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/dense/OimPoLxioYg/slide-001.html) - AI slide classifier: `content_slide` confidence `0.78` - Text source: none. - Slide text: not surfaced (`decorative` by AI classifier). ![[assets/dense-slides/OimPoLxioYg/slide-002.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/dense/OimPoLxioYg/slide-002.html) - AI slide classifier: `content_slide` confidence `0.97` - Text source: agent_vision. Slide text: > The Premise: Convince an AI you're the best artist > 1 GPT: Generate a prompt for users to draw > 2 User: Draws prompt in MS Paint interface > 3 CLIP: Judge vector similarity of text prompt and user image > 4 ???: 120k players in one week, 7 requests per second ![[assets/dense-slides/OimPoLxioYg/slide-003.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/dense/OimPoLxioYg/slide-003.html) - AI slide classifier: `content_slide` confidence `0.95` - Text source: agent_vision. Slide text: > Prompt: A Raccoon Driving a Tractor ![[assets/dense-slides/OimPoLxioYg/slide-004.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/dense/OimPoLxioYg/slide-004.html) - AI slide classifier: `content_slide` confidence `0.95` - Text source: agent_vision. Slide text: > Prompt: A Bumblebee that Loves Capitalism ![[assets/dense-slides/OimPoLxioYg/slide-005.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/dense/OimPoLxioYg/slide-005.html) - AI slide classifier: `content_slide` confidence `0.96` - Text source: advanced OCR `rapidocr-live/bright-screen/contrast`. - OCR decision: ready — Dense mixed text and diagram; better handled by OCR than manual transcription. Slide text: > How We're Using CLIP Go Deeper! > CLIP: Trained on 400M image/text pairs, OpenAl, 2021 > text_embedding: how CLIP Paint.wtf Scoring > mapsthepaint.wtfprompt into > its feature space Image_embedding: how CLIP maps the user submission into X of thePaint.wtfPrompt CLIP's Interpretation CLip'sInterpretation of User-Submitted Drawing > its feature space > distance between the prompt and the user drawing Winning paint.wtf: minimizing Cosine Similarity X ![[assets/dense-slides/OimPoLxioYg/slide-008.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/dense/OimPoLxioYg/slide-008.html) - AI slide classifier: `demo_video` confidence `0.95` - Text source: agent_vision. Slide text: > Draw a gorilla gardening with grapes ![[assets/dense-slides/OimPoLxioYg/slide-009.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/dense/OimPoLxioYg/slide-009.html) - AI slide classifier: `demo_video` confidence `0.95` - Text source: agent_vision. Slide text: > Draw a gorilla gardening with grapes ![[assets/dense-slides/OimPoLxioYg/slide-010.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/dense/OimPoLxioYg/slide-010.html) - AI slide classifier: `content_slide` confidence `0.99` - Text source: advanced OCR `rapidocr-live/bright-screen/opencv-adaptive`. - OCR decision: ready — dense comparison slide with small captions and example text; OCR is better for full extraction Slide text: > dmmnmhuiedbupina wosuossa Were all leaming here > CLIP Can Read > Draw a raccoon driving a tractor Gobs Rsnking: S86 cuA cf 10.187 ubmissiem Draw a raccoon driving a tractor Globst Rnking: 81 cit ot 10.187 swbmissioms A raccooh > TRACTOR > TRY AGAIN thoop crlr Geng Try AGAIn Rooe Wotr womg > 10 ![[assets/dense-slides/OimPoLxioYg/slide-012.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/dense/OimPoLxioYg/slide-012.html) - AI slide classifier: `content_slide` confidence `0.98` - Text source: advanced OCR `rapidocr-live/bright-screen/contrast`. - OCR decision: ready — dense bullet list and table are OCR-suitable; keep text field minimal in triage Slide text: > Lessons fromBuildingPaint.wtfwith CLIP We're all learning here > Roboflow Inference Makes Life Easy > Serving done right. model license > Built on the lessons of serving 1oom of API calls and thousands of hours of video. inference/eodels/clip interence/models/gaze inference/models/san Ml T, Apache 2.0 Apache 2.0 > Maximize throughput on your target inference/models/vit Apache 2.0 > hardware (GPU, CPU, edge) inference/models/yolact > Use ready-to-go foundation models interence/models/yolovs AGPL-30 > Pull in over 50k pretrained models from interence/eodels/yolov7 GPL-3.0 > Roboflow Universe community interence/models/yolovs AGPL-3.0 > 14 ### Hidden Non-Slide Evidence - [`slide-006.jpg`](/assets/dense-slides/OimPoLxioYg/slide-006.jpg) — `demo_video` confidence `0.96`; Stage composite with live demo screen, presenter footage, and sponsor logos; not a readable presentation slide. - [`slide-007.jpg`](/assets/dense-slides/OimPoLxioYg/slide-007.jpg) — `speaker_stage` confidence `0.17`; camera shot of speaker on stage with projected screen and sponsor logos; not a clean slide - [`slide-011.jpg`](/assets/dense-slides/OimPoLxioYg/slide-011.jpg) — `speaker_stage` confidence `0.16`; camera shot of speaker and projected slide; not a clean slide frame Classification audit: `raw/sources/slide-ai-classification/dense/OimPoLxioYg/audit.json`