Raw LLM Responses
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It's a terrible answer that lacks nuance. For example, atrophy of developer skil…
ytr_UgwTuWiUP…
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Let's make this clear. Deep fakes are not a crime the moment you post a photo of…
ytc_Ugwq6kDKS…
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I’m hooked on AI debates and talks. What a fascinating time to be alive with som…
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I think it was Larry Niven who first coined "A gentleman is someone who says tha…
ytc_UgwT2VP3H…
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week 4 she become self aware eats the chow mein you clearly said no then she co…
ytc_Ugxrrq_DA…
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The robot in the movie "2001 Space Odyssey" was amazing in what it could do then…
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These animated puppets with programmed responses are not at all in any way a thr…
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Ask it, "where do your ethics come from, and what moral values do you abide by..…
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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"}
]