I indexed 669 GB of my GoPro videos using my M1 Max computer and local ML models
TLDR: I had 2,207 GoPro videos, and I need to rewatch them to find interesting moments from my cycling journey. I built a project to index them locally on my M1 Max using open-source ML models, search for those moments, and send the best clips straight to my DaVinci Resolve timeline. I indexed 628 videos (668.68 GB, 15h 13m 18s of footage duration), more details in the metrics table in the last section of this article. Full article: https://iliashaddad.com/blog/i-indexed-669-gb-of-my-gopro-videos-using-my-m1-max-computer Comments URL: https://news.ycombinator.com/item?id=48528029 Points: 205 #
The increasing availability of powerful edge devices like the M1 Max and open-source ML models enables sophisticated local AI processing, making such personal projects feasible and efficient.
This demonstrates a growing trend towards localized and private application of advanced AI, potentially reducing reliance on cloud infrastructure for specific tasks and addressing privacy concerns.
Individuals can now perform complex media indexing and analysis tasks on personal hardware, moving beyond simple content creation to sophisticated organization and retrieval without external services.
- · Apple (M-series chips)
- · Open-source ML communities
- · Creative professionals
- · Privacy-focused individuals
- · Cloud-based indexing services
- · Centralized media management platforms
Increased adoption of local AI tools for media management and content creation workflows.
Development of more user-friendly applications leveraging local AI, further democratizing advanced processing capabilities.
A potential shift in data privacy expectations, as users realize more powerful processing can occur client-side without data ingress.
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Read at Hacker News — Front Page