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G @juliosantana1646 Humans do not need solar power in order to exist. We do not ne… ytr_UgyOGV90r… G Once they go full AI vision and AI targeting , it will become even more efficien… ytc_UgxnjqaLe… G I think my favorite example of this stuff comes from the analog horror community… ytc_Ugwdo1Ir2… G The world is going crazy wake up it's evil people off the world are evil ai Is g… ytc_UgzsxYc5Y… G Get all your money from your bank account before this AI code get's in producti… ytc_UgwePDAih… G I learned something about my own country in this video. I didnt know Denmark had… ytc_UgxuOB-gL… G Narayanan is like a religious leader... "But you need humans for..." Consistency… ytc_UgzY8R4WW… G Oh no i cant tell the diff between real and robot! 😂 really! Oh no were close to… ytc_Ugy_E_Hcr…

Comment

One note after watching this video - I see a fair number of people who seem to think that because LLMs seem to have encountered scaling issues that superintelligence or AGI is impossible. I'm not sure where exactly they get this idea, since LLMs are just one *type* of AI that has recently grown leaps and bounds. I expect that if LLMs do stagnate, something else or a new approach will show promise and that will become the next big thing. Who knows - the future is unpredictable, but I do think that Mixture of Experts ( MoE ) / component models that reach beyond language and additional tooling are going to greatly expand capabilities, and that there is a lot of room for optimization in both training and inference. I also feel it is quite important to emphasize that the philosophical argument about the nature of the machine ( true intelligence or understanding ) doesn't really matter - the outcome is what is important. The goal is to produce output that would normally require human intelligence. If it can sufficiently simulate whatever is required to outperform us in all assigned tasks, we've reached the point described.

youtube AI Moral Status 2025-11-13T17:3… ♥ 3

Coding Result

Dimension	Value
Responsibility	none
Reasoning	consequentialist
Policy	none
Emotion	indifference
Coded at	2026-04-26T23:09:12.988011

Raw LLM Response

[
{"id":"ytc_Ugwk2ueIr2Ap0ZOM14h4AaABAg","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"indifference"},
{"id":"ytc_UgxhjByikIT6XjelopB4AaABAg","responsibility":"user","reasoning":"deontological","policy":"regulate","emotion":"fear"},
{"id":"ytc_UgyQtMWSdPPGLWANyZR4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"ban","emotion":"approval"},
{"id":"ytc_Ugy-1rF-MAJhG79k3vd4AaABAg","responsibility":"ai_itself","reasoning":"unclear","policy":"none","emotion":"mixed"},
{"id":"ytc_UgzkF1yVTDQTJiH20Rx4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_Ugy5hK01GqmIAEfYY8B4AaABAg","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"indifference"},
{"id":"ytc_Ugw9tBSTa6sfDKd2xAd4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytc_UgxhdOUHZxhUFVI-Xu54AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"outrage"},
{"id":"ytc_UgwsxFMODuT1jE1doaZ4AaABAg","responsibility":"ai_itself","reasoning":"mixed","policy":"none","emotion":"fear"},
{"id":"ytc_UgzO7O3TgA2dFLjPz5Z4AaABAg","responsibility":"ai_itself","reasoning":"mixed","policy":"none","emotion":"approval"}
]

Raw LLM Responses