Raw LLM Responses
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This is how satan comes in stronger in th r world .Read your bibles 😮😮😮this is t…
ytc_UgxJnhVvV…
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2:03 Sophia looks soo terrific... This face looks like she's gonna take over hum…
ytc_UgxPPK8ek…
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This person is not an artist if they're having AI do the work that is an insult …
ytc_UgyTuQ0UR…
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every executive wanted him gone and did, it was Microsoft and investors who rein…
rdc_lpa9qxx
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What is important to note.. is where the music business was before AI. Becaus…
ytc_Ugwn7o6jm…
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@tylerbryden Yesterday the US President publically adressed concerns regarding A…
ytr_UgxDgQ4_N…
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You were probably thinking of the Gollum publishers having (allegedly) used AI …
ytr_UgwjrbMfw…
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@StefffennnnnI'm not going to say there are no benefits to cars. But none of w…
ytr_Ugxu88lil…
Comment
Eliezer's take on the 'paperclip maximizer' argument doesn't seem particularly applicable to current LLM architectures. When I ask ChatGPT for an answer, it neither gets stuck in an infinite loop nor produces endless responses in an attempt to 'maximize' its objective. Working with agents also involves setting constraints: we can specify a finite number of actions the model should run, and there's a system of permissions to accept or deny subroutine actions. It's unclear why Mr. Wolfram didn't tie this argument to known, practical AI procedures.
Also, if AGI truly achieves human-level general intelligence, it would presumably possess practical judgment capabilities. ChatGPT, for instance, provides finite responses rather than infinite outputs, and an AGI would theoretically have even more refined judgment. Just as adults have better risk assessment skills than children, an AGI should theoretically evaluate actions within realistic limits rather than pursuing infinite maximization of a single goal.
youtube
AI Governance
2024-11-13T16:0…
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | developer |
| Reasoning | consequentialist |
| Policy | none |
| Emotion | indifference |
| Coded at | 2026-04-27T06:24:53.388235 |
Raw LLM Response
[
{"id":"ytc_UgwfYHnRIec_UjaORrV4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"approval"},
{"id":"ytc_UgycnzNreGpB3a7a5Hp4AaABAg","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"indifference"},
{"id":"ytc_Ugzd-ma0ujZAb5HhHFp4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"mixed"},
{"id":"ytc_UgzsZtPkhMQCcCOmHgB4AaABAg","responsibility":"developer","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_UgxYn9JXLlg20G_a09d4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"outrage"},
{"id":"ytc_Ugz2_DwgYk7tALNnvm54AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"fear"},
{"id":"ytc_Ugwad4p8PY-nWvnjzPN4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"outrage"},
{"id":"ytc_Ugx0w3H6RV1sNvUp1ZV4AaABAg","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"mixed"},
{"id":"ytc_UgyR6_fTp_kjrcdO_SV4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytc_UgwxlrHOJKfspbgJ1TZ4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"mixed"}
]