Raw LLM Responses
Inspect the exact model output for any coded comment.
Look up by comment ID
Random samples — click to inspect
G
Hey Gabi thanks for this video. But AI art is so anonymous I saw the thumbnail o…
ytc_UgxrD_56f…
G
There are a lot of things wrong with it. First it seems that you are trying to c…
ytc_UgwfVXNsp…
G
I feel bad for the Ai dude, from what I see he didn't do anything bad…
ytc_UgzqUn0El…
G
I think it's likely that the people who follow AI frontier labs closely enough t…
rdc_o7vvmaq
G
what a well put together and thought out presentation. now lets ignore all these…
ytc_Ugwm1UIYJ…
G
Exactly. The issue is not automation. It’s as Bernie has said recently: the issu…
ytr_UgxqpAJJX…
G
Tell your AI to lie to you, believe the lie! If I tell chat gpt to pretend it's …
ytc_UgyIov8Gg…
G
Do you seriously expect AI to discern truth?? 🆘🆘🆘😭😭😭Please read the Bible yourse…
ytc_UgxE6a9SY…
Comment
We gotta stop giving tax perks to AI companies (and billionaires in general). Priorities upside down. No more data centers. Sam Altman is a bigger fraud than Elon Musk, and that's saying something.
AND YET we need subject matter experts in these cases. Lay end-users don't understand the tech. Eg Retrieval-Augmented Generation (RAG) is a technique to connect a Large Language Model (LLM) to external, authoritative knowledge sources outside of its original training data.
OpenAI models frequently use RAG to improve accuracy and provide up-to-date information. While the core GPT models are pre-trained, they are often combined with external data sources. ChatGPT uses retrieval to search the web when queries require current information.
Tldr : RAG enables OpenAI models (like all the popular models) to query trusted, external data sources, reducing hallucinations and allowing the AI to "know" information not present in its original training set.
Which is one reason you don't want courts regulating tech. The law is out of date within 9 months.
youtube
AI Responsibility
2026-04-11T15:0…
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | company |
| Reasoning | deontological |
| Policy | regulate |
| Emotion | outrage |
| Coded at | 2026-04-27T06:26:44.938723 |
Raw LLM Response
[
{"id":"ytc_UgwAqpAqIRbdOAfNvpJ4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_UgzukaGNMhrCBSOnZH14AaABAg","responsibility":"company","reasoning":"deontological","policy":"regulate","emotion":"outrage"},
{"id":"ytc_Ugy4nf5-kXagdaZTYXB4AaABAg","responsibility":"user","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_UgxuB2kOqqKk2ftCwAl4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytc_UgzvS-BxchBX1RdHqrF4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytc_UgyAMQKkOdp-RdCxUWd4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},
{"id":"ytc_UgziYRNo3eYs-i2W-Pp4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_UgwD_MhGljw1Q34faql4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytc_Ugx7wMNOowhCEfDNmPl4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytc_UgyxdxlpubZhWhdys_V4AaABAg","responsibility":"company","reasoning":"deontological","policy":"regulate","emotion":"outrage"}
]