Raw LLM Responses
Inspect the exact model output for any coded comment.
Look up by comment ID
Random samples — click to inspect
G
Intelligence has a direct negative correlation with anger and aggression. If an…
ytc_UgzKYKrTd…
G
God, I’m so sick of the argument of ai being more accessible. It is not owed to …
ytc_UgwdCN3PH…
G
AI is really cool, as in frontiers into true AI. Large language models and gener…
ytc_Ugwy_n8a5…
G
An the odds I use ai art I'm a project of mine I'll place very low…
ytr_UgxQtMRjK…
G
@Avenger222 artists are paid to teach all the time. That’s how a lot of artist m…
ytr_UgymmmcQ6…
G
Everyone makes a good point, but I do kinda wonder... is this that OP's version …
ytc_UgwRNm5le…
G
Dr. Jain’s explanation just clicked with me. Adapting to AI trends is crucial, j…
ytc_UgwKuusZz…
G
@Cronee333 As someone who's been working with AI to create short stories I disag…
ytr_UgwEYQ4Ps…
Comment
I'd like to see you explore the ramification of quantum computing specifically for the creation of Ai training \ data sets and onwards to Realtime analysis. It occurred to me that using QC as a generic computation engine and the unique but very narrow form of problems it can help with is a domain that AI could master very easily (problem formation and ramification analysis of the result). We would not really even need much of a technology upgrade from present for the AI to utilize the approach either for the problem selection or technically for the QC device itself.
It occurs to me that an AI looking to improve itself (or a more basic one programmed to) could use narrow scope analysis of QC to find optimal solutions to problems that would otherwise be computationally expensive. I feel that one AIQC will be about the last thing we every accomplish as after that all importent thinking will be outsourced.
youtube
AI Governance
2023-10-30T01:3…
♥ 46
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | none |
| Reasoning | consequentialist |
| Policy | none |
| Emotion | approval |
| Coded at | 2026-04-27T06:26:44.938723 |
Raw LLM Response
[
{"id":"ytc_UgwPh4abbPTk01ekasp4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_Ugzggv6ikwgryIrFlPN4AaABAg","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"mixed"},
{"id":"ytc_UgxDZP5RrShJ4zfCa2p4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},
{"id":"ytc_UgxQ17UN_r5YPN3xCpR4AaABAg","responsibility":"developer","reasoning":"consequentialist","policy":"none","emotion":"mixed"},
{"id":"ytc_UgwRfd10vvefaEdDOvp4AaABAg","responsibility":"distributed","reasoning":"deontological","policy":"unclear","emotion":"mixed"},
{"id":"ytc_UgwS5bxrsyki6c1lo8l4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},
{"id":"ytc_UgwCx6WRGFK10ibn5rl4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"fear"},
{"id":"ytc_Ugxlk1NNdA2C-zNOTwZ4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"fear"},
{"id":"ytc_Ugz1LWu60lvwsW28gWJ4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"mixed"},
{"id":"ytc_UgyuNRZGiRbenoaOw5t4AaABAg","responsibility":"none","reasoning":"deontological","policy":"none","emotion":"indifference"}
]