Raw LLM Responses

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@Trespasser68394 I happen to know math used for the back prop. It is just good old calculus with partial derivatives which is adjusting the weights of the neural net in order to minimize the error function between output and input. LLMs are just the good old neural nets from 70s, albeit with new groups of neurons (transformers, etc.) inside like scaled by a large number of elements which take a word and turn it into a numerical input, but back prop is still the same. Whether you have a simple MLP or a massive transformer, the goal is still to calculate errors. You still start at the end (the error) and work backward to the beginning. The back prop is a one shot deal per input/output. Once you show the input/output, the weights get adjusted. There is no any looping or continuous action (the back prop doesn't need that) unless some additional things are going on that they invented which is what I asked above and those who are employed by AI companies would know the answer.
youtube AI Moral Status 2026-03-02T19:2… ♥ 3
Coding Result
DimensionValue
Responsibilitynone
Reasoningunclear
Policynone
Emotionindifference
Coded at2026-04-27T06:24:53.388235
Raw LLM Response
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