So are people?
People are way more reliable.
LLMs are still surprisingly bad at some simple tasks
21–30 of 107 posts
Re: LLMs are still surprisingly bad at some simple tasks
#22> “To stave off some obvious comments: > yoUr'E PRoMPTiNg IT WRoNg! > Am I though?” Yes. You’re complaining that Gemini “shits the bed”, despite using 2.5 Flash (not Pro), without search or reasoning. It’s a fact that some models are smarter than others. This is a task that requires reasoning so the article is hard to take seriously when the author uses a model optimised for speed (not intelligence), and doesn’t even…
OP here. I literally opened up Gemini and used the defaults. If the defaults are shit, maybe don't offer them as the default? Or, if LLMs are so smart, why doesn't it say "Hmmm, would you like to use a different model for this?" Either way, disappointing.
> Or, if LLMs are so smart, why doesn't it say "Hmmm, would you like to use a different model for this?"
That is indeed an area where LLMs don't shine.
That is, not only are they trained to always respond with an answer, they have no ability to accurately tell how confident they are in that answer. So you can't just filter out low confidence answers.
Re: LLMs are still surprisingly bad at some simple tasks
#23Once again an example of "anti-ai people are those who treat LLMs as oracles, not the pro-ai people."
You mean the people who treat AI as it is advertised?
Re: LLMs are still surprisingly bad at some simple tasks
#24They are very good at some tasks and terrible at others. I use LLMs for language-related work (translations, grammatical explanations etc) and they are top notch in that as long as you do not ask for references to particular grammar rules. In that case they will invent non-existent references. They are also good for tutor personas: give me jj/git/emacs commands for this situation. But they are bad in other cases. I s…
I think Gemini is one of the best example of an LLM that is in some cases the best and in some cases truly the worst. I once asked it to read a postcard written by my late grandfather in Polish, as I was struggling to decipher it. It incorrectly identified the text as Romanian and kept insisting on that, even after I corrected it: "I understand you are insistent that the language is Polish. However, I have carefully…
I find that surprising, actually. Gemini is VERY good with Sanskrit and a few other Indian languages. I would expect it to have completely mastered European languages.
Re: LLMs are still surprisingly bad at some simple tasks
#25The point from the end of the post that AI produces output that sounds correct is exactly what I try to emphasize to friends and family when explaining appropriate uses of LLMs. AI is great at tasks where sounding correct is the essence of the task (for example "change the style of this text"). Not so great when details matter and sounding correct isn't enough, which is what the author here seems to have rediscovered…
> When LLMs say something true, it’s a coincidence of the training data that the statement of fact is also a likely sequence of words;
Do you know what a "coincidence" actually is? The definition you're using is wrong.
It's not a coincidence that I train a model on healthcare regulations and it answers a question about healthcare regulations correctly.
None of that is coincidental.
If I trained it on healthcare regulations and asked it about recipes, it won't get anything right. How is that coincidental?
Re: LLMs are still surprisingly bad at some simple tasks
#26https://chatgpt.com/share/68cffaab-4c14-8006-89a2-1818172e4d...
Tried on ChatGPT, seems fine.
Re: LLMs are still surprisingly bad at some simple tasks
#27>This is a pretty simple question to answer. Take two lists and compare them. This continues a pattern as old as home computing: The author does not understand the task themselves, consequently "holds the computer wrong", and then blames the machine. No "lists" were being compared. The LLM does not have a "list of TLDs" in its memory that it just refers to when you ask it. If you haven't grokked this very fundamental…
That’s the point the author is making. The LLMs don’t have the raw correct information required to accomplish the task so all they can do is provide a plausible sounding answer. And even if it did the way they are architected still can only results in a plausible sounding answer.
Re: LLMs are still surprisingly bad at some simple tasks
#28They are very good at some tasks and terrible at others. I use LLMs for language-related work (translations, grammatical explanations etc) and they are top notch in that as long as you do not ask for references to particular grammar rules. In that case they will invent non-existent references. They are also good for tutor personas: give me jj/git/emacs commands for this situation. But they are bad in other cases. I s…
Just use Pillow and python.
It is the only way to do real image work these days, and as a bonus LLMs suck a lot less at giving you nearly useful python code.
The above is a bit of a lie as opencv has more capabilities, but unless you are deep in the weeds of preparing images for neural networks pillow is plenty good enough.
Re: LLMs are still surprisingly bad at some simple tasks
#29> “To stave off some obvious comments: > yoUr'E PRoMPTiNg IT WRoNg! > Am I though?” Yes. You’re complaining that Gemini “shits the bed”, despite using 2.5 Flash (not Pro), without search or reasoning. It’s a fact that some models are smarter than others. This is a task that requires reasoning so the article is hard to take seriously when the author uses a model optimised for speed (not intelligence), and doesn’t even…
OP here. I literally opened up Gemini and used the defaults. If the defaults are shit, maybe don't offer them as the default? Or, if LLMs are so smart, why doesn't it say "Hmmm, would you like to use a different model for this?" Either way, disappointing.
You are pointing out a maturity issue, not a capability problem. It's clear to everyone that LLM products are immature, but saying they are incapable is misleading
Re: LLMs are still surprisingly bad at some simple tasks
#30Don't use a microwave to fry a steak then. This is an irritating post and I have plenty of skepticism towards AI. LLMs were always bad at this kind of task, simple to us humans as it may be. This post proves nothing that wasn't known for two years.
However, I do superficially agree with some of the links at the end. LLMs as they have been so far are confirmation machines and it does take skill to use them effectively. Or knowing when not to use them.