Raw LLM Responses
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G
I even find the fuzzy jankiness of it all so much funnier than the Ai slop…
ytr_UgySlCw4R…
G
well we can make the working robots have no emotion so they can just do there jo…
ytc_UgjUKMnhf…
G
I love how we can test AI a lot faster thanks to using TTS, just out of "typing …
ytc_UgxF4neG0…
G
Oh, you mean it is not real life... yet! The smarter people understand that we a…
ytr_Ugy9PCtTB…
G
Well, Marcel Duchamp said it, right? Something about a chair....
In any case, ju…
ytc_UgwpCFCUE…
G
So sad that I'm LMAO. You guy's are so far behind the CCP that if it were possib…
ytc_UgxpVbpjq…
G
I love using A.I. art generators but will not use any model trained specific to …
ytc_UgySsxb4q…
G
They don't need help per se; they need "permission". Both S. Korea and Japan.
A…
rdc_dkzpwyv
Comment
Watching this, it’s fascinating to see Hinton defend the 2015 Distillation paper as a 'groundbreaking' feature, but we have to credit Tomas Mikolov (2013) for the real breakthrough.
For decades, the 'Godfathers' (Hinton, Bengio) were stuck on complex, biologically-inspired models that were too slow for the real world—basically building a 'map of a nonexistent planet.' Mikolov was the one who looked at these 'abandoned ideas,' stripped away the unnecessary complexity, and found the 'last piece of the puzzle.'
While Hinton provided the 'Deep Learning' philosophy, Mikolov’s Word2Vec proved that Simplicity + Scale > Complex Theory. If Science is a relay race, Hinton defined what 'running' was, but he was carrying a heavy backpack of theory. Mikolov dropped the backpack and actually reached the finish line. We shouldn't debase the 'Engineer' just because the 'Architect' had the theory first—without the engine, the blueprints are just paper. For those who want to see that breakthrough paper so successful that it actually convinced Google and OpenAI to pour billions into the "Scaling Hypothesis"—the idea that if we just make these simple models bigger, they will become "conscious.
youtube
AI Moral Status
2026-03-03T20:4…
♥ 1
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | none |
| Reasoning | unclear |
| Policy | unclear |
| Emotion | indifference |
| Coded at | 2026-04-27T06:24:53.388235 |
Raw LLM Response
[
{"id":"ytc_UgwgDFT8k8IzqiZLoYZ4AaABAg","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"indifference"},
{"id":"ytc_UgyzylnXaFMmtrLGOrt4AaABAg","responsibility":"ai_itself","reasoning":"mixed","policy":"unclear","emotion":"fear"},
{"id":"ytc_UgwieH700oj6qjfbf9Z4AaABAg","responsibility":"ai_itself","reasoning":"mixed","policy":"unclear","emotion":"fear"},
{"id":"ytc_Ugyysel8LcOQ2RhaNCF4AaABAg","responsibility":"unclear","reasoning":"deontological","policy":"unclear","emotion":"mixed"},
{"id":"ytc_UgzYicYEDPPUtpkOAbN4AaABAg","responsibility":"unclear","reasoning":"mixed","policy":"unclear","emotion":"approval"},
{"id":"ytc_UgyHURv3w59WU-3rReV4AaABAg","responsibility":"developer","reasoning":"deontological","policy":"unclear","emotion":"outrage"},
{"id":"ytc_Ugz11qCRxfFx2T0zkgN4AaABAg","responsibility":"ai_itself","reasoning":"unclear","policy":"unclear","emotion":"mixed"},
{"id":"ytc_UgzR0Vr7zpuJigXeM8x4AaABAg","responsibility":"developer","reasoning":"deontological","policy":"unclear","emotion":"indifference"},
{"id":"ytc_UgwzDg52y6HzYuGs6XV4AaABAg","responsibility":"user","reasoning":"virtue","policy":"unclear","emotion":"mixed"},
{"id":"ytc_UgympM97wvWODhcOf414AaABAg","responsibility":"developer","reasoning":"consequentialist","policy":"ban","emotion":"outrage"}
]