Raw LLM Responses

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Small note. It’s not that chatbots change throughout the day, it’s that they use something we call “temperature” that makes them nondeterministic. Temperature is just a knob that tells the model how “loose” it can get when picking the next token. At temperature 0, it always chooses the highest-probability token, so you get the same output every time. As you turn the temperature up, you’re basically saying “sample from the distribution instead of locking into the top choice.” That introduces randomness. Same prompt, same model, but now the model is allowed to pick from a wider set of plausible next tokens, so the output can diverge run to run. But we can’t use a zero temperature and have deterministic output because multiple tokens can have the same probabilities, so some level of randomness is needed. On top of this, ChatGPT cranks the temperature to make it more “engaging.” That’s why you can get drastically different responses from one day to the next. It’s literally impossible to get consistency because of the way LLMs work.
youtube AI Harm Incident 2025-11-25T01:4… ♥ 2
Coding Result
DimensionValue
Responsibilitynone
Reasoningunclear
Policyunclear
Emotionindifference
Coded at2026-04-27T06:24:53.388235
Raw LLM Response
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