this post was submitted on 08 Feb 2024
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This looks more like a floating point issue than a mistake an LLM would make
There are no LLMs involved in this picture, to train an llm you'd need 100x the training data. The panel is about a normal ML model.
The training data here is exaggerated more, actually. This task should take kilobytes, max, and would finish in a fraction of a second. Also, no self-respecting ML engineer would put together an ML system without accounting for every data type.