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by verdverm
927 days ago
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With fine-tuning, you can get really good results on specific tasks that can run on regular cpu/mem. I'd suggest looking into the distillation research, where large model expertise can be transferred to much smaller models. Also, an LLM trained to be good at this task has many more applications than just turning command output into structured data. It's actually one of the most compelling business use cases for LLMs |
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You have a small C program that processes this data in memory, and dumps it to stdout in tabular text format.
Rather than simplify by stripping out the problematic bit (the text output), you suggest adding a large, cutting-edge, hard to inspect and verify piece of technology that transforms that text through uncountable floating point operations back into differently-formatted UTF8.
It might even work consistently (without you ever having 100% confidence it won't hallucinate at precisely the wrong moment).
You can certainly see it being justified for one-off tasks that aren't worth automating.
But to shove such byzantine inefficiency and complexity into an engineered system (rather than just modify the original program to give the format you want) offends my engineering sensibilities.
Maybe I'm just getting old!