[AlienRobot]

I'm no AI fan, but articles talking about the shortcomings of LLM's seem to have to be complaining that forks aren't good for drinking soup.

Don't use LLM's to do 2 + 2. Don't use LLM's to ask how many r's are in strawberry.

For the love of God. It's not actual intelligence. This isn't hard. It just randomly spits out text. Use it for what it's good at instead. Text.

Instead of hunting for how to do things in programming using an increasingly terrible search engine, I just ask ChatGPT. For example, this is something I've asked ChatGPT in the past:

    in typescript, I have a type called IProperty<T>, how do I create a function argument that receives a tuple of IProperty<T> of various T types and returns a tuple of the T types of the IProperty in order received?

This question that's such an edge case that I wasn't even sure how to word properly actually yielded the answer I was looking for.

    function extractValues<T extends readonly IProperty<any>[]>(
      props: [...T]
    ): { [K in keyof T]: T[K] extends IProperty<infer U> ? U : never } {
      return props.map(p => p.get()) as any;
    }

This doesn't look unrealiable to me. It actually feels pretty useful. I just need [...T] there and infer there.

[DanHulton]

The thing is, I have spent the last year being told that I will VERY SOON be able to use a fork to drink soup, and better than any spoon has ever been able to, and in fact pretty soon spoons will be completely outclassed anyway, and I'M the idiot for doubting this.

Articles like this are still very much needed, to push back against that narrative, regularly, until it DOES become as obvious to everyone as it is to you.

[AlienRobot]

My impression is that the only people telling others they can drink soup with forks are the people who sell the forks.

Even this isn't new. A few years ago we had people who sold knives telling everybody you could use knives to drink soup. And in some cases they weren't even kitchen knives, they were switchblades.

[bluefirebrand]

> Don't use LLM's to do 2 + 2. Don't use LLM's to ask how many r's are in strawberry

But use them to do more important things that require more precision and accuracy?

No thanks

[batshit_beaver]

You use LLMs to _discover_ how to approach important problems. You don't necessarily need to use the output verbatim. Same as StackOverflow and Google.

[yongjik]

When you employ your developers at $200K/yr you won't trust them to tell you the first one hundred digits of pi, but you'll trust them with your business logic, which is much more important and mission-critical to you.

Same thing.

[bluefirebrand]

The difference is that (hopefully) your employee is honest enough to say "I do not know the first 100 digits of Pi offhand but I can find out"

An LLM will happily produce a string of 100 digits that might be the first 100 digits of Pi, might be some known sequence of 100 digits in Pi but not the first 100, or might be 100 random digits that have nothing to do with Pi

[empath75]

I was actually curious about this and chatgpt actually accurately and very slowly gave me the first 100 digits of pi one digit at a time. I have _no idea_ how that worked, it did not search, nor did it run code. As far as I can tell, it pulled it straight out of it's own model.

If I ask it to use python, it writes and executes the code _much_ more quickly, same if I ask it to search.

[coliveira]

The problem is exactly how the public will learn "not to ask 2+2". When you have a well trained professional using an LLM it's all great. They know how to separate hallucination from actually good results as you do. The problem lies with the general public and new workers who will, no questions about it, use the AI generated results as some sort of truth.

[AlienRobot]

Maybe use an LLM to detect when the public is asking the wrong question and display a message saying "As a large language model, I don't know how to count."

[Marazan]

People need to stop recommending forks to drink soup with.

[uludag]

So many times I've asked questions just like this and gotten complete nonsense incorrect answers. In fact, you have no guarantees whatsoever that even the typescript question you asked will always return a sensible answer.

I'm by no means saying that LLMs aren't useful. They're just not reliably useful.