Raw LLM — Corpus Dashboard

Look up by comment ID

Random samples — click to inspect

G Hey Tim. What If AI took even 1 minute of your show over 10,000 plus shows in a … ytc_UgzpcR9np… G No shit lol , AI learned from the best , the human animal and are bad qualities … ytc_UgzsWj0gP… G What really bugs me about the medical industry is that they do not want people g… ytc_Ugzy0_rXd… G If there was no blur to compensate for the robot overlay, it be a flawless edit… ytc_UgwRTeGkF… G isn't the term" super intelligence" in as of itself at the very least speculativ… ytc_UgwWQ9h_y… G The idea of a "robot tax" makes a lot of sense to me, not for the reasons indica… ytc_UgxTwZNRa… G My recent interactions with artificial intelligences has convinced me that they … ytc_Ugx5UrvNN… G This. So much. I'm super Christian and I started TRYING to get AI to talk like J… rdc_mljylh6

Comment

@wesleywyndam-pryce5305 or it may as well mean you use it wrong) Not that i think that i write good code) If you actually use it to generate clear cut and small snippets it gets quite the good job of naming and applying algorythms give or take a small cleanup. If you are trying to generate big code blocks or complex ideas that actually require way more than just applying something you may find in a book or documentation for the thing you are using - then sure it will generate pure garbage most of the time(but sometimes it even works, so it can be ocassionally usefull, though in my practice it takes more to refactor it than to just decomposit the task yourself and make the ai do the "busy work" of doing verbose and somewhat "clean" code). Its also good at translating unsearchable queries like "that bus that is used to control and communicate with displays in mobile phones"(not the best example, but you get the jist of it, trying to find the term based on its vague qualities that any human fammiliar with it could identify) or something vague like that, which would take some time to actually get the answer.

youtube AI Jobs 2024-07-04T20:4… ♥ 1

Coding Result

Dimension	Value
Responsibility	user
Reasoning	mixed
Policy	none
Emotion	approval
Coded at	2026-04-27T06:24:59.937377

Raw LLM Response

[
{"id":"ytr_Ugyz60ptxYe4IIXiWop4AaABAg.A4pycgvXdNnA5Eb-akDfHX","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"indifference"},
{"id":"ytr_Ugws8ZnRO9bBg9kV0IN4AaABAg.A4okjhk8d4vAUVP8_sN9t4","responsibility":"distributed","reasoning":"consequentialist","policy":"regulate","emotion":"fear"},
{"id":"ytr_UgzBOXooJ-09ERpsSFR4AaABAg.A4o-X-cOQvCA5USGjS46Wb","responsibility":"user","reasoning":"mixed","policy":"none","emotion":"approval"},
{"id":"ytr_UgzBOXooJ-09ERpsSFR4AaABAg.A4o-X-cOQvCA6krFRfGF1l","responsibility":"user","reasoning":"mixed","policy":"none","emotion":"mixed"},
{"id":"ytr_UgzBOXooJ-09ERpsSFR4AaABAg.A4o-X-cOQvCA8G9ngCff9_","responsibility":"user","reasoning":"mixed","policy":"none","emotion":"approval"},
{"id":"ytr_UgwxJi1fiXILjEAcJA14AaABAg.A4joCxX6lVyA4ukpHSO7_q","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"approval"},
{"id":"ytr_UgwxJi1fiXILjEAcJA14AaABAg.A4joCxX6lVyA4xhjxhZlJE","responsibility":"user","reasoning":"mixed","policy":"none","emotion":"mixed"},
{"id":"ytr_UgxwSPgZsOGpesmz0gB4AaABAg.A4jePxGkQcLA4jfBe7VVJw","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"indifference"},
{"id":"ytr_UgwsrsRca6eHSSTjcxF4AaABAg.A4iqFAu0QMzA5JKFDgvk-0","responsibility":"user","reasoning":"mixed","policy":"industry_self","emotion":"fear"},
{"id":"ytr_UgyuRPbyjoH2w2kXIXp4AaABAg.A4iPdyNvnu2A4jcTDVBhq9","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"outrage"}
]

Raw LLM Responses