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UID:pretalx-ringzer0-bootstrap24-austin-NXCUE3@cfp.ringzer0.training
DTSTART;TZID=CST:20240224T100000
DTEND;TZID=CST:20240224T104500
DESCRIPTION:The world is awash in large-language model (LLM) AI (e.g.\, Cha
 tGPT) news\, predictions\, and of course\, content (all for good and ill).
  This talk takes a step back from the posturing and hype to look at how th
 ese models work\, and how to detect the content they produce. We will look
  at the fundamentals of LLM-generated text detection\, compare the best in
  breed: GPTZero\, Roberta\, etc. detector with a novel detector\, ZipPy.\n
 ZipPy is a new\, open-source LLM text detector (and attribution tool!) dev
 eloped by Thinkst Labs that is 60-100x faster than the competition\, over 
 1000x smaller (< 200KB)\, and for many types of content\, more accurate. W
 e will explain the intuition behind ZipPy\, show how it works\, and they t
 ypes of content it struggles with. Finally we look at where LLMs can impro
 ve their stealth\, and fundamental shortcomings in their designs that enab
 le detection long-term.
DTSTAMP:20260615T082258Z
LOCATION:Track 1 📍 Auditorium 1.110
SUMMARY:Exploring the lay of the LLM detection landscape - Jacob Torrey
URL:https://cfp.ringzer0.training/ringzer0-bootstrap24-austin/talk/NXCUE3/
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