this post was submitted on 05 Feb 2025
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This is a bad example.. If I ask a friend "is strawberry spelled with one or two r's"they would think I'm asking about the last part of the word.
The question seems to be specifically made to trip up LLMs. I've never heard anyone ask how many of a certain letter is in a word. I've heard people ask how you spell a word and if it's with one or two of a specific letter though.
If you think of LLMs as something with actual intelligence you're going to be very unimpressed.. It's just a model to predict the next word.
This is exactly the problem, though. They don’t have “intelligence” or any actual reasoning, yet they are constantly being used in situations that require reasoning.
What situations are you thinking of that requires reasoning?
I've used LLMs to create software i needed but couldn't find online.
Creating software is a great example, actually. Coding absolutely requires reasoning. I’ve tried using code-focused LLMs to write blocks of code, or even some basic YAML files, but the output is often unusable.
It rarely makes syntax errors, but it will do things like reference libraries that haven’t been imported or hallucinate functions that don’t exist. It also constantly misunderstands the assignment and creates something that technically works but doesn’t accomplish the intended task.
I think coding is one of the areas where LLMs are most useful for private individuals at this point in time.
It's not yet at the point where you just give it a prompt and it spits out flawless code.
For someone like me that are decent with computers but have little to no coding experience it's an absolutely amazing tool/teacher.
Maybe if you focus on pro- or anti-AI sources, but if you talk to actual professionals or hobbyists solving actual problems, you'll see very different applications. If you go into it looking for problems, you'll find them, likewise if you go into it for use cases, you'll find them.
Personally I have yet to find a use case. Every single time I try to use an LLM for a task (even ones they are supposedly good at), I find the results so lacking that I spend more time fixing its mistakes than I would have just doing it myself.
So youve never used it as a starting point to learn about a new topic? You've never used it to look up a song when you can only remember a small section of lyrics? What about when you want to code a block of code that is simple but monotonous to code yourself? Or to suggest plans for how to create simple sturctures/inventions?
Anything with a verifyable answer that youd ask on a forum can generally be answered by an llm, because theyre largely trained on forums and theres a decent section the training data included someone asking the question you are currently asking.
Hell, ask chatgpt what use cases it would recommend for itself, im sure itll have something interesting.
No. I've used several models to "teach" me about subjects I already know a lot about, and they all frequently get many facts wrong. Why would I then trust it to teach me about something I don't know about?
No, because traditional search engines do that just fine.
See this comment.
I guess I've never tried this.
Kind of, but here's the thing, it's rarely faster than just using a good traditional search, especially if you know where to look and how to use advanced filtering features. Also, (and this is key) verifying the accuracy of an LLM's answer requires about the same about of work as just not using an LLM in the first place, so I default to skipping the middle-man.
Lastly, I haven't even touched on the privacy nightmare that these systems pose if you're not running local models.
Artificial sugar is still sugar.
Artificial intelligence implies there is intelligence in some shape or form.
Exactly. The naming of the technology would make you assume it's intelligent. It's not.
Because it contains sucrose, fructose or glucose? Because it metabolises the same and matches the glycemic index of sugar?
Because those are all wrong. What's your criteria?
In this example a sugar is something that is sweet.
Another example is artificial flavours still being a flavour.
Or like artificial light being in fact light.
Something that pretends or looks like intelligence, but actually isn't at all is a perfectly valid interpretation of the word artificial - fake intelligence.
Thats because it wasnt originally called AI. It was called an LLM. Techbros trying to sell it and articles wanting to fan the flames started called it AI and eventually it became common dialect. No one in the field seriously calls it AI, they generally save that terms to refer to general AI or at least narrow ai. Of which an llm is neither.