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by famouswaffles
656 days ago
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My point is that for some bizare reason, people have standards of reasoning (for machines) that only exist in fiction or their own imagination. It is beyond silly to dump an architecture for a limitation the human brain has. A reasoning engine that can iterate indefinitely with no external aid does not exist in real life. That the transformer also has this weakness is not any reason for it to have capabilities less than a brain so it's completely moot. |
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It shouldn't be surprising they are not great at reasoning, or everything one would hope for from an AGI, since they simply were not built for that. If you look at the development history, the transformer was a successor to LSTM-based seq-2-seq models using Bahdanau attention, whose main goal was to more efficiently utilize parallel hardware by supporting parallel processing. Of course a good language model (word predictor) will look as if it's reasoning because it is trying to model the data it was trained on - a human reasoner.
As humans we routinely think for seconds/minutes or even hours before speaking or acting, while an LLM only has that fixed N steps (layers) of computation. I don't know why you claim this difference (among others) should make no difference, but it clearly does, with out-of-training-set reasoning weakness being a notable limitation that people such as Demis Hassabis have recently conceded.