Raw LLM Responses
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G
This is actually a reason why AI should not be available to the public. So disgu…
ytc_UgzSl8BUa…
G
This will create a self fulfilling prophecy… telling people that there’s no futu…
ytc_UgzGBdPFn…
G
Interesting read. It does seem to overlook the impact of the post Black Death pe…
rdc_o6i3d5m
G
I'm not entirely confident that AI is as great as it's being pushed to be. Perh…
ytc_Ugx4WKaEY…
G
Copilot is actually better at handling FEs and else disturbed minds. Tell it you…
ytc_UgzuVsuca…
G
Yes, last year my garden was infested by slugs. There are none this year. 😊…
ytr_UgwQHuHZq…
G
I appreciate the sentiment of Miyazaki. But realistically, AI will be a powerful…
ytc_UgywXqnit…
G
He's "now" worried about AI? He's been worried about it for 10 years, and that's…
ytc_UgzerODfm…
Comment
NO, NO , NO... What people call “AGI” right now is mostly marketing. LLMs and “agents” are useful, but they are not general intelligence. LLMs scale with a clear problem: you burn vastly more compute for smaller gains. That diminishing return matters because it turns “just scale it” into a power and cost wall. A system that needs huge GPU farms to get marginal improvements is not on a clean path to human level general intelligence. And the “agent” layer doesn’t fix the core issue. Agents are task loops: call the model, check output, call tools, retry, patch failures, repeat. That can reduce hallucinations by adding filters and verification steps, but it’s still a brittle routine. It’s closer to automated workflow than a mind. Iterating until you get a coherent answer is not the same as understanding, learning, or reasoning robustly across new situations. So yes, LLMs have a scaling and efficiency problem, and agents are mostly a wrapper that compensates for weaknesses. That combination can produce impressive demos, but it’s not AGI.
youtube
2026-02-06T09:4…
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | none |
| Reasoning | consequentialist |
| Policy | none |
| Emotion | outrage |
| Coded at | 2026-04-27T06:24:53.388235 |
Raw LLM Response
[
{"id":"ytc_UgxULa83FZ45v4baS4B4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"approval"},
{"id":"ytc_UgxOMcz4ECaofmsxYRB4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"unclear","emotion":"fear"},
{"id":"ytc_UgyAHji4ybUbrw9hApl4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"outrage"},
{"id":"ytc_Ugyq-wZA5h8aqDzbkXB4AaABAg","responsibility":"none","reasoning":"deontological","policy":"none","emotion":"indifference"},
{"id":"ytc_UgybcsHqzXzMqgDQFIR4AaABAg","responsibility":"ai_itself","reasoning":"contractualist","policy":"unclear","emotion":"mixed"},
{"id":"ytc_UgxDEk5XLRAtwFS0dIV4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"outrage"},
{"id":"ytc_UgxYrnJRGPMuJMah83x4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"none","emotion":"outrage"},
{"id":"ytc_Ugw4SY4f03fOfKYHNhx4AaABAg","responsibility":"developer","reasoning":"virtue","policy":"none","emotion":"resignation"},
{"id":"ytc_UgyRQzKHHbaaOgtfcDR4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"regulate","emotion":"hope"},
{"id":"ytc_UgxYsTz43jL9j9D914F4AaABAg","responsibility":"none","reasoning":"deontological","policy":"none","emotion":"indifference"}
]