Markdown source

Dense Slides: How fast are LLM inference engines anyway? — Charles Frye, Modal

Source Video

How fast are LLM inference engines anyway? — Charles Frye, Modal

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

• Recreated text/layout view: open HTML recreation
• AI slide classifier: content_slide confidence 0.98
• Text source: none.
• OCR decision: ready — Dense product/UI screenshot with chart, small labels, and configuration text; OCR is better than manual transcription.
• Slide text: not surfaced (illegible by AI classifier).

• Recreated text/layout view: open HTML recreation
• AI slide classifier: content_slide confidence 0.98
• Text source: agent_vision.
• OCR decision: ready — Dense product/UI screenshot with chart, controls, and small configuration text; OCR is better than manual transcription.

Slide text:

LLM Engine Advisor

Classification audit: raw/sources/slide-ai-classification/dense/DeFF3J8T5Pk/audit.json