Raw LLM Responses

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G AI can read so should you stop to learn reading how to read?? Should AI read boo… ytc_Ugz5FtFe-… G That's ridiculous, you just forced him to affirm you. You can use manipulations … ytc_Ugwigj-yV… G honestly this guy is a dumbass, saying that drawing doesn't make you an artist l… ytc_UgwsYpUI6… G it's not about "wanting to end the conversation" it's because for the AI ​​it ga… ytr_UgyUWwn45… G Well, smart people, please give your best to develop a new vaccine asap - we are… rdc_hm7geqf G Human inteligence created the technology to fly, and them used this technology t… ytc_UgzXFO_xz… G It's interesting how, once released, an AI becomes an object of learning for oth… ytc_UgzU9v2GC… G @mariselachapa646yes I have but like I said we are far out from A.I replacing mo… ytr_Ugz19ifqx…
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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