--- title: "Reconstructed Slides: Dream Machine: Scaling to 1m users in 4 days — Keegan McCallum, Luma AI" category: "slides" video_id: "EY4O9M6AsWI" sourceLabels: ["Cropped public YouTube video frames", "Local OpenCV slide-region detection", "Local RapidOCR"] --- # Reconstructed Slides: Dream Machine: Scaling to 1m users in 4 days — Keegan McCallum, Luma AI ## Source Video [Dream Machine: Scaling to 1m users in 4 days — Keegan McCallum, Luma AI](https://www.youtube.com/watch?v=EY4O9M6AsWI) ## Method This deck is reconstructed from the existing video frame captures by detecting likely slide regions with OpenCV, cropping/upscaling those regions, deduplicating similar crops, and OCRing the cropped slide images locally. It is a cleaner companion to the full-stage frame deck. ## Reconstructed Slides ![[assets/reconstructed-slides/EY4O9M6AsWI/slide-003.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/reconstructed/EY4O9M6AsWI/slide-003.html) - AI slide classifier: `content_slide` confidence `0.94` - Text source: agent_vision. Slide text: > AIE > Luma > Microsoft > smol.ai ![[assets/reconstructed-slides/EY4O9M6AsWI/slide-004.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/reconstructed/EY4O9M6AsWI/slide-004.html) - AI slide classifier: `content_slide` confidence `0.93` - Text source: none. - OCR decision: ready — dense embedded social post screenshot with small text ![[assets/reconstructed-slides/EY4O9M6AsWI/slide-005.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/reconstructed/EY4O9M6AsWI/slide-005.html) - AI slide classifier: `content_slide` confidence `0.94` - Text source: none. - OCR decision: ready — dense chat screenshot collage with small text ![[assets/reconstructed-slides/EY4O9M6AsWI/slide-006.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/reconstructed/EY4O9M6AsWI/slide-006.html) - AI slide classifier: `content_slide` confidence `0.99` - Text source: agent_vision. Slide text: > Luma's mission is to build multimodal general intelligence that can generate, understand, and operate in the physical world ![[assets/reconstructed-slides/EY4O9M6AsWI/slide-009.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/reconstructed/EY4O9M6AsWI/slide-009.html) - AI slide classifier: `title_card` confidence `0.98` - Text source: agent_vision. Slide text: > Public API > Check it out at: > https://lumalabs.ai/api/pricing ![[assets/reconstructed-slides/EY4O9M6AsWI/slide-010.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/reconstructed/EY4O9M6AsWI/slide-010.html) - AI slide classifier: `content_slide` confidence `0.92` - Text source: advanced OCR `rapidocr-live/bright-screen/contrast` reconciled by agent. - OCR decision: ready — Dense repeated diagram labels are better handled by OCR than direct transcription. Slide text: > AIE > CPU Worker > triton-inference-server > CPU Worker > triton-inference-server > CPU Worker > triton-inference-server > CPU Worker > triton-inference-server > CPU Worker > triton-inference-server > CPU Worker > triton-inference-server > Luma > Microsoft > smol ai ![[assets/reconstructed-slides/EY4O9M6AsWI/slide-011.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/reconstructed/EY4O9M6AsWI/slide-011.html) - AI slide classifier: `content_slide` confidence `0.99` - Text source: advanced OCR `rapidocr-live/bright-screen/contrast` reconciled by agent. - OCR decision: ready — Body bullets are small and dense enough that OCR is the safer extraction path. Slide text: > Challenges > - Brittle, need to coordinate between both CPU and Triton being up at the same time > - Triton not built for multi-gpu/multi-node > - Push model not ideal for multi-node (which node has rank 0?) > - No/limited support for non-nvidia chipsets with Triton > - Very difficult to develop against > - Need to have every piece everywhere, hard to bring in disparate compute (i.e. from our training cluster :kekw:) ![[assets/reconstructed-slides/EY4O9M6AsWI/slide-012.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/reconstructed/EY4O9M6AsWI/slide-012.html) - AI slide classifier: `content_slide` confidence `0.91` - Text source: advanced OCR `rapidocr-live/border-trim/contrast` reconciled by agent. - OCR decision: ready — Dense architecture diagram labels and connectors are better suited to OCR than direct transcription. Slide text: > API > Redis (standby) > Redis > Redis (standby) > GPU Workers > CPU Workers > Seaweedfs ![[assets/reconstructed-slides/EY4O9M6AsWI/slide-013.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/reconstructed/EY4O9M6AsWI/slide-013.html) - AI slide classifier: `content_slide` confidence `0.99` - Text source: agent_vision. Slide text: > Challenges > - Backpressure > - Priorities/fair scheduling > - Handling many different models > - Handling Bursts ![[assets/reconstructed-slides/EY4O9M6AsWI/slide-014.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/reconstructed/EY4O9M6AsWI/slide-014.html) - AI slide classifier: `title_card` confidence `0.96` - Text source: agent_vision. Slide text: > Queues, Queues, Queues ![[assets/reconstructed-slides/EY4O9M6AsWI/slide-015.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/reconstructed/EY4O9M6AsWI/slide-015.html) - AI slide classifier: `title_card` confidence `0.98` - Text source: agent_vision. Slide text: > Model Management ![[assets/reconstructed-slides/EY4O9M6AsWI/slide-016.jpg]] - Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/reconstructed/EY4O9M6AsWI/slide-016.html) - AI slide classifier: `title_card` confidence `0.97` - Text source: agent_vision. Slide text: > THANK YOU ### Hidden Non-Slide Evidence - [`slide-001.jpg`](/assets/reconstructed-slides/EY4O9M6AsWI/slide-001.jpg) — `sponsor_logo` confidence `0.99`; sponsor logo wall, no presentation content - [`slide-002.jpg`](/assets/reconstructed-slides/EY4O9M6AsWI/slide-002.jpg) — `speaker_stage` confidence `0.98`; speaker on stage, not a slide - [`slide-007.jpg`](/assets/reconstructed-slides/EY4O9M6AsWI/slide-007.jpg) — `demo_video` confidence `0.99`; embedded video footage, not a presentation slide - [`slide-008.jpg`](/assets/reconstructed-slides/EY4O9M6AsWI/slide-008.jpg) — `demo_video` confidence `0.99`; embedded video footage, not a presentation slide - [`slide-017.jpg`](/assets/reconstructed-slides/EY4O9M6AsWI/slide-017.jpg) — `speaker_stage` confidence `0.99`; Camera shot of speaker, audience, and projected screen; not a presentation slide. Classification audit: `raw/sources/slide-ai-classification/reconstructed/EY4O9M6AsWI/audit.json`