Raw LLM Responses
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G
This was such an important TD Talk. I cant believe I just recently found out abo…
ytc_UgwKQF7KX…
G
with AI, it’s souless. people spend years learning art, unlike AI who just gener…
ytc_UgwBWtWam…
G
who cares what u tell ai no one will ever know it’s worst to tell ppl u know who…
ytc_UgyttW5lf…
G
the american govt has access to the best ai's,highest tech, yet problems with ec…
ytc_Ugw0iqwXH…
G
At least you tried, if it would happened faster and we had less idiots that deci…
rdc_hm7g4h0
G
cool to see how people try to fool it, but i still run my content through Winsto…
ytc_UgxMLIZPS…
G
Bro is in his own world, ai isn't something that could think, its just a super c…
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G
Tsunami of slop IS accurate. Have you seen the AI cat videos that are literally …
ytc_Ugz9QDFCn…
Comment
How they talk about them in this episode is a bit odd/buzzwordy. Basically when you use ChatGPT and give it a sentence “I am a person” the sentence is “tokenized” into an input to a model. A really bad tokenizer would be each character is a token so the above message would be 13 tokens (including spaces).
“Get ahold of these tokens” like they say in the video is odd because it makes it sound like they’re pre-generated. Each LLM model would have its own associated tokenizer, but where you do the conversion between “I am a human” and its tokenized form + passing it thru the model + output detokenization could lower cost.
When you send a message to ChatGPT it runs its tokenizer on your input, which is run on some hardware. So tokens are “limited” because this processing has to happen somewhere & algorithms for tokenization can be more/less efficient.
youtube
AI Governance
2026-04-22T21:0…
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | none |
| Reasoning | consequentialist |
| Policy | none |
| Emotion | mixed |
| Coded at | 2026-04-27T06:24:59.937377 |
Raw LLM Response
[
{"id":"ytr_Ugw74p-SZWXhLmxc8tx4AaABAg.AVrz6YaJ9_LAVsZ_cneu1O","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytr_Ugw74p-SZWXhLmxc8tx4AaABAg.AVrz6YaJ9_LAVtBm1oSq5q","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"mixed"},
{"id":"ytr_UgwOm45dO_GAdfVgNQx4AaABAg.AVrZJAemr9VAVst0rq6CI-","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytr_Ugyho4YAo19NPbyQ-wt4AaABAg.AVrR7e1QWsOAVrfAKKueRY","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},
{"id":"ytr_Ugyho4YAo19NPbyQ-wt4AaABAg.AVrR7e1QWsOAVrkvh1QBdY","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytr_UgyaoldSKD4I6ePNLqR4AaABAg.AVrNNBxi0BDAVrjhQyjwXI","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytr_UgyfPdsytKUVZ6h6EXx4AaABAg.AVrL5aBaoIWAVs-hqoNNbI","responsibility":"company","reasoning":"deontological","policy":"liability","emotion":"outrage"},
{"id":"ytr_UgyfPdsytKUVZ6h6EXx4AaABAg.AVrL5aBaoIWAVs2oL7SWna","responsibility":"company","reasoning":"mixed","policy":"none","emotion":"mixed"},
{"id":"ytr_Ugx3s9ARYK8prO-gkWN4AaABAg.AVrKlv9UZ_eAVupGvsTl-H","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"indifference"},
{"id":"ytr_Ugx3s9ARYK8prO-gkWN4AaABAg.AVrKlv9UZ_eAVvCEl8zZ9B","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"mixed"}
]