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[ARTICLE · art-162137] src=news.ycombinator.com ↗ pub= topic=machine-learning verified=true sentiment=↑ positive

I indexed 37h of my YouTube library using an RTX 4090 and local ML models in 24h

Iliashad indexed 37 hours and 38 minutes of his own YouTube video library in 24 hours and 13 minutes of total compute time using the self-hosted Docker version of his project on a rented RTX 4090, he reported on Hacker News. Frame analysis consumed roughly 85% of the processing time, with the TextDetection plugin the heaviest load on coding and screen recordings and FaceRecognition the heaviest on podcasts.

by read1 min views1 publishedNov 1, 2026

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| | Hacker Newsnew |past |comments |ask |show |jobs |submit | login | | | | I indexed 37h of my YouTube library using an RTX 4090 and local ML models in 24h | | | | 2 points by iliashad19 minutes ago |hide |past |favorite |3 comments | | | | TLDR: I indexed 37 hours and 38 minutes of my videos using the self-hosted Docker version of my project on a rented RTX 4090 - Total compute time: 24 hours 13 minutes - Frame analysis took ~85% of the time - Heaviest plugins: TextDetection (especially on coding/screen recordings) and FaceRecognition (on podcasts) Full article here: https://iliashaddad.com/blog/i-indexed-37h-of-my-youtube-library-using-an-rtx-4090-and-local-ml-models-in-24h |

source & further reading
news.ycombinator.com — original article Anthropic's Mythos-class model allegedly leaked on Hugging Face A simpler way to put ChatGPT to work (A shared allowance for ChatGPT and Codex) Tell HN: Claude Code now defaults to Haiku 5.5
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