Raw LLM Responses
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@SoggyMicrowaveNugget You’re out here acting like you’re single-handedly saving …
ytr_UgwcC_wLd…
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Should AI agents be granted bank accounts? Well they already do, they have acces…
ytc_Ugz6yo1yI…
G
Chickens number in the trillions because they are useful. If humans become the c…
ytc_UgwdVjJNF…
G
I think you never saw Bing Sydney prompt. It's huge Like, 3x the size of this lo…
rdc_kop1esp
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What's the point of introducing something like ChatGPT if they are just going to…
rdc_jhcneme
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Cheers! Tbh, it gave this first try! First exchange in this particular chat actu…
rdc_kvt3hfo
G
Take humanity out of learning and you produce kids with no humanity. Gifted tea…
ytc_Ugx4GGbxN…
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Trumpians are the death squad. They want to rule and be served. They do not wa…
ytc_UgzEIt3RQ…
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"}
]