2mo ago

LLMs and their efficiency, can they really replace humans?

arxiv.org

Evaluating the Energy-Efficiency of the Code Generated by LLMs

AI bros won't hype this up for the news for sure, but 480x energy doesn't sound optimistic enough for replacement.

10 comments

LLMs don't have reasoning nor internal logic. If you take a look at the "thinking" feature AIs like Gemini introduced, this becomes even more obvious. In order to have the most basic type of analysis possible, it must hallucinate an entire context window to force the language model to reach a specific conclusion.
There's zero world in which LLMs replace humans. They might, temporarily, be convincing enough to trick a few CEOs... But that period of time won't last long.
Now, a human being assisted by AI on Microsoft Word or their Python IDE, sure.
- extrapolate. what in 10 years?
  
  If they're still LLMs? Nothing much changes.
  
  or rather ask ai, it can give a better answer than me. xD
I'm not sure about the significance of this preprint. Writing energy-efficient sorting algorithms and lab course example code is a very specific problem. It doesn't say a lot about AI in general. Also: Did they forget to tell the AI it's supposed to write energy-efficient code? I didn't read the entire paper. But the prompt example doesn't look like it's in there.
I don't value these papers very highly. Before they are even published/peer reviewed, the landscape have changed. Models get better quickly, agentic frameworks too, and their code even more. But good to have a ball-park measurement tho.
If we see what is coming from the latest papers, ('discover ai' on the tube), we have only scratched the surface of how this is going to pan out. Buckle up..
LLMs are great at automating tasks where we know the solution. And there are a lot of workflows that fall in this category. They are horrible at solving new problems, but that is not where the opportunity for LLMs is anyway.
the reality is that we will just produce more powaaaaa for ai.

10 comments