# I am the Watcher. I am your guide through this vast new twtiverse.
#
# Usage:
# https://watcher.sour.is/api/plain/users View list of users and latest twt date.
# https://watcher.sour.is/api/plain/twt View all twts.
# https://watcher.sour.is/api/plain/mentions?uri=:uri View all mentions for uri.
# https://watcher.sour.is/api/plain/conv/:hash View all twts for a conversation subject.
#
# Options:
# uri Filter to show a specific users twts.
# offset Start index for quey.
# limit Count of items to return (going back in time).
#
# twt range = 1 2
# self = https://watcher.sour.is/conv/113905526603538716
(highlighted by the @fsf@fsf):
#Maintainers are drowning in junk bug reports written by machine learning models #ml
"While low-grade and frustrating online materials have been a problem for many years (long before chat bots entered cyberspace), machine learning models have significantly boosted the quantity of illegitimate reports. Even for those who don't use machine learning models, #developers who #maintain projects must still spend valuable time and resources investigating any potentially valid reports received, including those created by machine learning models. Not only is investigating these junk reports a waste of time, but it may also increase maintainer #burnout and lead to a smaller population of people involved in #security work. If you are a #bug submitter, avoid submitting anything without first having human eyes verifying it."
#AI #freesoftware
The original article: https://www.theregister.com/2024/12/10/ai_slop_bug_reports/
(highlighted by the @fsf@fsf):
#Maintainers are drowning in junk bug reports written by machine learning models #ml
"While low-grade and frustrating online materials have been a problem for many years (long before chat bots entered cyberspace), machine learning models have significantly boosted the quantity of illegitimate reports. Even for those who don't use machine learning models, #developers who #maintain projects must still spend valuable time and resources investigating any potentially valid reports received, including those created by machine learning models. Not only is investigating these junk reports a waste of time, but it may also increase maintainer #burnout and lead to a smaller population of people involved in #security work. If you are a #bug submitter, avoid submitting anything without first having human eyes verifying it."
#AI #freesoftware
The original article: https://www.theregister.com/2024/12/10/ai_slop_bug_reports/