Original Summary

I've been working on something called SeleKyT. The idea came from a problem I kept coming back to with long-form video: Finding a clip isn't necessarily the hard part. Understanding which moments actually matter is. Give an AI a two-hour interview, podcast, documentary, lecture, or conversation and it's relatively easy to find moments where someone says something interesting. But a useful first edit needs more than that. It needs to understand: what the conversation is actually about which moments belong together what's repetitive where the story changes direction which moments provide context what should actually survive the edit That's what I'm trying to build with SeleKyT. The goal isn't to replace the editor. It's to make the editor's first pass dramatically faster. The system takes long-form footage and produces an editorial starting point — identifying potential stories, organizing relevant moments, shaping a first-pass sequence, and preparing outputs for different formats. One of the biggest things I've learned while building it is that trust matters more than automation. If an AI says "this is the best moment" but can't give you a meaningful reason, the editor is still doing the hardest part: figuring out whether the AI is right. So I'm putting a lot of effort into making the decisions inspectable rather than treating the result like a black box. It's still early. There are parts I haven't validated in real production environments yet, and multilingual footage has already exposed some interesting problems. I'm curious about something from people who actually edit long-form content: What would an AI need to understand before you'd trust it to make your first cut? Not the final edit — just the first pass.   submitted by   /u/bhairava0 [link]   [comments]

  • 情报分类：工作与职业机会
  • 分类依据：内容涉及招聘、求职或职业发展
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/22 04:14:53