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0 pointsparentheses3y ago0 comments

This may be an implementation detail to obfuscate GPT weights. OR it was to encourage selecting the best answers to further train the model.

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textninja3y ago

Pseudo random numbers are injected into the models via its temperature settings, but OpenAI could seed that to get the same answers with the same input. I’m going out on a limb here with pure speculation but given the model, a temperature, and a known text prompt, OpenAI could probably reverse engineer a seed and prove that the weights are the same.

slt20213y ago

fine-tuning original weights solves that, and any sane person would fine-tune for their task anyways to get better results

textninja3y ago

Since fine-tuning is often done by freezing all but the top layers I wonder if it would still be possible to take a set of inputs and outputs and mathematically demonstrate that a model is derivative of ChatGPT. There may well be too much entropy to unpack, but I’m sure there will be researchers exploring this, if only to identify AI-generated material.

Of course, since the model is so large and general purpose already, I can’t assume the same fine-tuning techniques are used as for vastly smaller models, so maybe layers aren’t frozen at all.

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textninja3y ago

slt20213y ago

fine-tuning original weights solves that, and any sane person would fine-tune for their task anyways to get better results

textninja3y ago

Of course, since the model is so large and general purpose already, I can’t assume the same fine-tuning techniques are used as for vastly smaller models, so maybe layers aren’t frozen at all.

j / k navigate · click thread line to collapse