Raw LLM Responses
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G
The complete marginalization and eventual elimination of the lower classes via A…
ytc_UgyB_wFrL…
G
"God" said reproduce
"AI" say reduce...
All commandments of that 1 group that th…
ytc_UgxV1dx_E…
G
Nothing can replace human artwork. The AI just uses the original ones and mix th…
ytc_UgxFQvCXz…
G
I drove for three decades. Trucking is heavily regulated. The companies should…
ytr_UgwPL_XeD…
G
You're not making art by using ai. You're asking ai to make it for you…
ytr_UgxF2duvi…
G
People who play games ARE doing scripted content. What do you think games are? I…
ytc_Ugwm-sKgN…
G
Riggggghhhtttt.. because AI requires religion or any other faith derived social …
ytc_UgwNxFlGP…
G
I think that there will be a point where AI creates amazing super customised con…
rdc_m5lnsxd
Comment
The irony is that the AI providers use a system of "Tokens" as they call them which are the prompt you've given it broken up into little subsegments of language that it processes as individual data packets and the words like "Please" and "Thank you" are entirely discarded by the processing stage of the inferencing algorithm. This is why companies like Open AI for instance have publicly asked people to stop using "Please" and "Thank You" because it costs them millions of dollars a month when it's just useless information that is discarded for the inferencing phase, but they still have to pay the cost of the API calls and the data centers and energy costs required to process those useless bits of information that just get overlooked and discarded by the algorithm anyways. So your advice is actually incorrect, you are correct to say that AI models have gotten better at mimicking different personalities or expertise through agentic AI modelling, but even when using an agentic AI model it's still much more efficient to not use manners or interjections and be as concise with your prompts as possible to net the best results as a response.
youtube
AI Moral Status
2025-05-18T07:3…
♥ 1
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | company |
| Reasoning | consequentialist |
| Policy | none |
| Emotion | mixed |
| Coded at | 2026-04-27T06:26:44.938723 |
Raw LLM Response
[{"id":"ytc_UgzieYAVd79dfS1T3oN4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"regulate","emotion":"fear"},
{"id":"ytc_UgygjXpgj9eeRpzF9k54AaABAg","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"approval"},
{"id":"ytc_UgybG9byOUCN0Kq0nY54AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"none","emotion":"mixed"},
{"id":"ytc_UgxbsJJTeG4u9LPYb4Z4AaABAg","responsibility":"developer","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_UgybO7KTwWbaTe-uJvt4AaABAg","responsibility":"ai_itself","reasoning":"mixed","policy":"none","emotion":"fear"},
{"id":"ytc_UgzR38lXgQTe5bGv99d4AaABAg","responsibility":"none","reasoning":"deontological","policy":"none","emotion":"indifference"},
{"id":"ytc_UgyMvVO4dgzzWAo2T2B4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"approval"},
{"id":"ytc_UgzwtPdbB2JDj9Bee2t4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"none","emotion":"mixed"},
{"id":"ytc_UgyaLfn7CwrW2Ccn34B4AaABAg","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"approval"},
{"id":"ytc_Ugxts3C5FwXiLSrgiId4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"resignation"}]