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"all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4."
"systems more powerful than GPT-4"
By what metric are we determining it to be "more powerful". That term is ambiguous within the context of machine learning. Are they talking about any system which has an MAE lower than GPT-4 on a given dataset?
No self-respecting AI dev can say "more powerful" with a straight face.
I assume they'd use pure computational power, measurable access to amount of data, # of processors / ram / computations done per interaction, number of interactions etc. There's a number of models to describe an AI's power that I've seen, unfamiliar with their specific names though.
I assume
In this case, you assume incorrectly.
pure computational power, measurable access to amount of data, # of processors / ram / computations done per interaction
No. Those are ambiguous methods of determining a models performance. What you described indicates computational/data efficiency. Absolutely none of those metrics indicate the performance of a models output. To do that, one needs 1) a reference dataset and 2) a loss/reward metric or some ensamble of them. Computational efficiency has zero correlation to model performance.
I do this for a living.
I do this for a living.
Bring back Tay, faggot.
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