Raw LLM Responses
Inspect the exact model output for any coded comment.
Look up by comment ID
Random samples — click to inspect
G
Those people that run, the stock market are completely illiterate people that da…
ytc_UgybQ5KPN…
G
ah bro AI is gonna blow the lid off the lies entrenched on this planet..its just…
ytc_Ugxl9iKfR…
G
Honestly I've been telling AI chuds that it costs next to nothing to pick up a p…
ytc_Ugz01MXBY…
G
Also, when AI inevitably develops a consciousness, you’ll be sorry you treated i…
ytc_Ugz01MXEl…
G
As it stands right now, it's a cool party trick, but AI's ability to engineer co…
ytc_UgyMtlXWz…
G
In the end if big companies automated everything and everybody lost their jobs, …
ytc_Ugx_pr_w4…
G
mocking someone who is just asking for help is really crappy behavior you guys d…
ytc_UgzJ9JsX-…
G
I know this is an eye for an eye but what if the females did the exact same thi…
ytc_UgyDMZInc…
Comment
before dropping my comment here who I am, I m a software engineer and a neural network engineer for 6 years now. so this is true, we develop most of the machine learning models like image detection and pattern detections but AI like chatGPT trained on 1.24T (trillions) amount of data so it can be anything but when it's come to a LLM (large language model) developers finetune them and put some rules on the main core so developers can manipulate the model as they want. for example chatGPT and gemini is more friendly while Grok is more flirty. but if we run the model without any finetunning or without any rules, now that's the situation comes upside down. for example in chatGPT they check before the model response is it nsfw content or not. it's on the core and that's why people can't brake it but sometimes some people manage to do that. in theory is if we run a model without that rules layer. it can be anything, and that's dark
youtube
AI Moral Status
2026-01-22T10:4…
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | developer |
| Reasoning | consequentialist |
| Policy | industry_self |
| Emotion | indifference |
| Coded at | 2026-04-27T06:26:44.938723 |
Raw LLM Response
[{"id":"ytc_UgyJxTwvrk_nnq0f7Mt4AaABAg","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"approval"},
{"id":"ytc_UgyPsc7-l4MCpx2ymat4AaABAg","responsibility":"developer","reasoning":"consequentialist","policy":"industry_self","emotion":"indifference"},
{"id":"ytc_Ugz7kz8dlw42wbRQ5S14AaABAg","responsibility":"ai_itself","reasoning":"deontological","policy":"unclear","emotion":"outrage"},
{"id":"ytc_UgwGOADygqc8L-qMl7V4AaABAg","responsibility":"distributed","reasoning":"consequentialist","policy":"unclear","emotion":"fear"},
{"id":"ytc_UgwMpC-PZBZT5mwpjoB4AaABAg","responsibility":"ai_itself","reasoning":"deontological","policy":"regulate","emotion":"outrage"},
{"id":"ytc_UgzJ190IKZpLvLWLSWt4AaABAg","responsibility":"developer","reasoning":"consequentialist","policy":"liability","emotion":"fear"},
{"id":"ytc_UgzZiuw259EEA7ds75t4AaABAg","responsibility":"company","reasoning":"deontological","policy":"regulate","emotion":"outrage"},
{"id":"ytc_UgwNWwI7cOdQ1iHG6id4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_Ugw1hJ65iKsTegvcJHd4AaABAg","responsibility":"user","reasoning":"mixed","policy":"unclear","emotion":"mixed"},
{"id":"ytc_Ugww5RPRSXwetYx74Kd4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"unclear","emotion":"fear"}]