Raw LLM Responses

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G In a way the predicted ai boom and doom is a manifestation of the misguided ideo… ytc_UgwX1CAYG… G Trump and the kardashians doesn’t need an AI algorithm, they are already deep de… ytc_UgzyZtYw1… G 44:13 Not sure why anyone is talking about the Venus project. There is a founda… ytc_Ugx2lHUQ5… G Elon Musk should never be sane washed. Stop buying his products and make him go… ytc_UgxGqAG2e… G As if people who make, buy and sell weapons of mass destruction care one iota as… ytc_Ugy8RD2CK… G That robot became SELF AWARE in that very moment! It started thinking for itself… ytc_UgwJBnN3c… G Glad to hear this discussion take place. Unmasking AI was an insightful read. Re… ytc_UgyF6vpF5… G We must banished these heretics that use A.I art Just for the greatest creation … ytc_UgwIxxV4x…
Comment
You should also mention the objective bottleneck of LLMs: all of their learning is squeezed through the single objective of next-token prediction. Large language models are trained to predict the next word (or token) given the previous context. No matter how complex the task appears—reasoning, summarizing, coding, or answering philosophical questions—the underlying training objective is always the same: maximize the probability of the next token. This creates a structural bottleneck. Because everything must be optimized through this single objective, the model is not directly trained to “know,” “understand,” or “reason” in the human sense. Instead, it learns statistical patterns that help it continue text in a way that resembles high-quality human responses. Any reasoning ability, uncertainty expression (such as saying “I don’t know”), or structured problem-solving emerges indirectly from this next-token training objective rather than being explicitly optimized for truth or calibrated uncertainty.
youtube AI Moral Status 2026-03-01T12:5… ♥ 2
Coding Result
DimensionValue
Responsibilitynone
Reasoningunclear
Policyunclear
Emotionindifference
Coded at2026-04-27T06:24:53.388235
Raw LLM Response
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