alt Hacker NewsI feel like you didn't understand the goal of this study
> The DTN-UK stated earlier this year that generic LLMs must never be used as autonomous advisory calculators for insulin delivery. This data is the quantitative evidence base for that statement.
This study is to prove that you should not rely on LLMs
Replies
that is good to know. presented this way i find LLM behavior to be a feature, not a bug. then again i think everything is value add over pen and paper / notepad / spreadsheet and maybe a friend or doctor (or specialized equipment if you need more than calorie in, calorie out). just go exercise and don't be a lard lad
The paper itself is a lot clearer about the purpose. The blog post reads very clickbaity and doesn't really explain the context well.
But it's stupid. If i smack myself in the head with a hammer is that proof hammers shouldn't be relied on?
The thing is it doesn't really prove LLMs can't do this, it proves no existing frontier LLMs can do this.
The part where they talk about sampling multiple runs is interesting - it suggests to me that in the next few years as the reasoning process is improved the models may be able to do that autonomously.
My mind really is going to using a dedicated object detection models fine-tuned with nutrition information, but I don't think there's a fundamental reason LLMs can't eventually manage this use case, except perhaps the size of the needed weights being prohibitively large.