alt.hn

3/27/2025 at 9:22:42 PM

I genuinely don't understand why some people are still bullish about LLMs

https://twitter.com/skdh/status/1905132853672784121

by ksec

3/28/2025 at 12:20:57 AM

I get so confused on this. I play around, test, and mess with LLMs all the time and they are miraculous. Just amazing, doing things we dreamed about for decades. I mean, I can ask for obscure things with subtle nuance where I misspell words and mess up my question and it figures it out. It talks to me like a person. It generates really cool images. It helps me write code. And just tons of other stuff that astounds me.

And people just sit around, unimpressed, and complain that ... what ... it isn't a perfect superintelligence that understands everything perfectly? This is the most amazing technology I've experienced as a 50+ year old nerd that has been sitting deep in tech for basically my whole life. This is the stuff of science fiction, and while there totally are limitations, the speed at which it is progressing is insane. And people are like, "Wah, it can't write code like a Senior engineer with 20 years of experience!"

Crazy.

by gilbetron

3/28/2025 at 11:23:23 AM

The technology is not just less than superintelligence, for many applications it is less than prior forms of intelligence like traditional search and Stack Exchange, which were easily accessible 3 years ago and are in the process of being displaced by LLMs. I find that outcome unimpressive.

And this Tweeter's complaints do not sound like a demand for superintelligence. They sound like a demand for something far more basic than the hype has been promising for years now. - "They continue to fabricate links, references, and quotes, like they did from day one." - "I ask them to give me a source for an alleged quote, I click on the link, it returns a 404 error." (Why have these companies not manually engineered out a problem like this by now? Just do a check to make sure links are real. That's pretty unimpressive to me.) - "They reference a scientific publication, I look it up, it doesn't exist." - "I have tried Gemini, and actually it was even worse in that it frequently refuses to even search for a source and instead gives me instructions for how to do it myself." - "I also use them for quick estimates for orders of magnitude and they get them wrong all the time. " - "Yesterday I uploaded a paper to GPT to ask it to write a summary and it told me the paper is from 2023, when the header of the PDF clearly says it's from 2025. "

by WhyOhWhyQ

3/28/2025 at 11:55:57 AM

A municipality in Norway used LLM to create a report about the school structure in the municipality (how many schools are there, how many should there be, where should they be, how big should they be, pros and cons of different size schools and classes etc etc). Turns out the LLM invented scientific papers to use as references and the whole report is complete and utter garbage based on hallucinations.

by Thlom

3/28/2025 at 12:15:33 PM

And that says… what? The entire LLM technology is worthless for all applications, from all implementations?

A company I worked for spent millions on a customer service solution that never worked. I wouldn’t say that contracted software is useless.

by brookst

3/28/2025 at 1:24:04 PM

I agree. I use LLMs heavily for gruntwork development tasks (porting shell scripts to Ansible is an example of something I just applied them to). For these purposes, it works well. LLMs excel in situations where you need repetitive, simple adjustments on a large scale. IE: swap every postgres insert query, with the corresponding mysql insert query.

A lot of the "LLMs are worthless" talk I see tends to follow this pattern:

1. Someone gets an idea, like feeding papers into an LLM, and asks it to do something beyond its scope and proper use-case.

2. The LLM, predictably, fails.

3. Users declare not that they misused the tool, but that the tool itself is fundamentally corrupted.

It in my mind is no different to the steam roller being invented, and people remaking how well it flattens asphalt. Then a vocal group trying to use this flattening device to iron clothing in bulk, and declaring steamrollers useless when it fails at this task.

by icepat

3/28/2025 at 2:15:31 PM

>swap every postgres insert query, with the corresponding mysql insert query.

If the data and relationships in those insert queries matter, at some unknown future date you may find yourself cursing your choice to use an LLM for this task. On the other hand you might not ever find out and just experience a faint sense of unease as to why your customers have quietly dropped your product.

by replyifuagree