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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

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.

nancyminusone 2y ago
No, it says that people dislike liars. If you are known for making up things constantly, you might have a harder time gaining trust, even if you're right this time.
- sswatson 2y ago
  All of these things can be true at the same time: 1. LLMs have been massively overhyped, including by some of the major players. 2. LLMs have significant problems and limitations. 3. LLMs can do some incredibly impressive things and can be profoundly useful for some applications. I would go so far as to say that #2 and #3 are hardly even debatable at this point. Everyone acknowledges #2, and the only people I see denying #3 are people who either haven't investigated or are so annoyed by #1 that they're willing to sacrifice their credibility as an intellectually honest observer.
  - absolutelastone 2y ago
    #3 can be true and yet not be enough to make your case. Many failed technologies achieved impressive engineering milestones. Even the harshest critic could probably brainstorm some niche applications for a hallucination machine or whatever.
- fragmede 2y ago
  And yet we keep electing them to public office.
svrtknst 2y ago
You, and the OP, are being unfair in your replies. Obviously, it's not worthless for all applications but when LLMs obviously fail in disastrous ways in some important areas, you can't refute that by going "actually it gives me codign advice and generates images". Thats nice and impressive, but there are still important issues and shortcomings. Obligatory, semirelated xkcd: https://xkcd.com/937/ https://xkcd.com/937/
icepat 2y ago
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.
- replyifuagree 2y ago
  >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.
  - actinium226 2y ago
    Probably better to have AI help you write a script to translate postgres statements to mysql
  - babyent 2y ago
    I hope people do this and royally mess shit up. Maybe then they’ll snap out of it. I’ve already seen people completely mess things up. It’s hilarious. Someone who thinks they’re in “founder mode” and a “software engineer” because chatgpt or their cursor vomited out 800 lines of python code.
    - brookst 2y ago
rzwitserloot 2y ago
It mostly says that one of the seriously difficult challenges with LLMs is a meta-challenge: * LLMs are dangerously useless for certain domains. * ... but can be quite useful for others. * The real problem is: They make it real tricky to tell, because most of all they are trained to sound professional and authoritative. They hallucinate papers because that's what authoritative answers look like. That already means I think LLMs are far less useful than they appear to be. It doesn't matter how amazing a technology is: If it has failure modes and it is very difficult to know what they are, it's dangerous technology no matter how awesome it is when it is working well. It's far simpler to deal with tech that has failure modes but you know about them / once things start failing it's easy to notice. Add to it the incessant hype, and, oh boy. I am not at all surprised that LLMs have a ridiculously wide range as to detractors/supporters. Supporters of it hype the everloving fuck out of it, and that hype can easily seem justified due to how LLMs can produce conversational, authoritative sounding answers that are explicitly designed to make your human brain go: Wow, this is a great answer! ... but experts read it and can see the problems there. Which lots of tech suffers from: as a random example: Plenty of highly upvoted apparently fantastically written Stack Overflow answers have problems. For example, it's a great answer... for 10 years ago; it is a bad idea today because the answer has been obsoleted. But between the fact that it's overhyped and particularly complex to determine an LLM answer is hallucinated drivel, it's logical to me that experts are hyperbolic when highlighting the problems. That's a natural reaction when you have a thing that SEEMS amazing but actually isn't.
- fragmede 2y ago
  > Stack Overflow answers have problems. For example, it's a great answer... for 10 years ago To be fair, that's a huge problem with stack overflow and its culture. A better version of stack overflow wouldn't have that particular issue.
dmichulke 2y ago
It says we don't have a lower bound on the effectiveness. It's (currently) like an ad saying "this product can improve your stuff up to 300%"
knowitnone 2y ago
If it makes data up, then it is worthless for all implementations. I'd rather it said I don't have info on this question.
- joquarky 2y ago
  > all implementations Are you speaking for yourself or everyone?
- anamexis 2y ago
  It only makes it worthless for implementations where you require data. There's a universe of LLM use cases that aren't asking ChatGPT to write a report or using it as a Google replacement.
  - timacles 2y ago
    The problem is that yes llms are great when working on some regular thing for the first time. You can get started at a speed never before seen in the tech world. But as soon as your use case goes beyond that LLMs are almost useless. The main complaint that yes its extremely helpful in that specific subset of problems, it’s not actually pushing human knowledge forward. Nothing novel is being created with it. It has created this illusion of being extremely helpful when in reality it is a shallow kind of help.
- deleted 2y ago
  [deleted]
- brookst 2y ago
  Does “it” apply to Homo sapiens as well?
- tasuki 2y ago
  > If it makes data up, then it is worthless for all implementations. Not true. It's only worthless for the things you can't easily verify. If you have a test for a function and ask an LLM to generate the function, it's very easy to say whether it succeeded or not. In some cases, just being able to generate the function with the right types will mostly mean the LLM's solution is correct. Want a `List(Maybe a) -> Maybe(List(a))`? There's a very good chance a LLM will either write the right function or fail the type check.
camillomiller 2y ago
That software just didn‘t work that way. I don’t think it tried to convince the users that they were wrong by spouting nonsense that seems legitimate.
mywittyname 2y ago
It says that people need training on what the appropriate use-cases for LLMs are. This is not the type of report I'd use an LLM to generate. I'd use a database or spreadsheet. Blindly using and trusting LLMs is a massive minefield that users really don't take seriously. These mistakes are amusing, but eventually someone is going to use an LLM for something important and hallucinations are going to be deadly. Imagine a pilot or pharmacist using an LLM to make decisions. Some information needs to come from authoritative sources in an unmodified format.
michaelcampbell 2y ago
> And that says… what? The entire LLM technology is worthless for all applications, from all implementations? You're the first in the thread to have brought that up; there are far more charitable ways to have interpreted the post you're replying to.

nancyminusone 2y ago

No, it says that people dislike liars. If you are known for making up things constantly, you might have a harder time gaining trust, even if you're right this time.

sswatson 2y ago
All of these things can be true at the same time: 1. LLMs have been massively overhyped, including by some of the major players. 2. LLMs have significant problems and limitations. 3. LLMs can do some incredibly impressive things and can be profoundly useful for some applications. I would go so far as to say that #2 and #3 are hardly even debatable at this point. Everyone acknowledges #2, and the only people I see denying #3 are people who either haven't investigated or are so annoyed by #1 that they're willing to sacrifice their credibility as an intellectually honest observer.
- absolutelastone 2y ago
  #3 can be true and yet not be enough to make your case. Many failed technologies achieved impressive engineering milestones. Even the harshest critic could probably brainstorm some niche applications for a hallucination machine or whatever.
fragmede 2y ago
And yet we keep electing them to public office.

svrtknst 2y ago

You, and the OP, are being unfair in your replies. Obviously, it's not worthless for all applications but when LLMs obviously fail in disastrous ways in some important areas, you can't refute that by going "actually it gives me codign advice and generates images". Thats nice and impressive, but there are still important issues and shortcomings. Obligatory, semirelated xkcd: https://xkcd.com/937/ https://xkcd.com/937/

icepat 2y ago

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.

replyifuagree 2y ago
>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.
- actinium226 2y ago
  Probably better to have AI help you write a script to translate postgres statements to mysql
- babyent 2y ago
  I hope people do this and royally mess shit up. Maybe then they’ll snap out of it. I’ve already seen people completely mess things up. It’s hilarious. Someone who thinks they’re in “founder mode” and a “software engineer” because chatgpt or their cursor vomited out 800 lines of python code.
  - brookst 2y ago

rzwitserloot 2y ago

It mostly says that one of the seriously difficult challenges with LLMs is a meta-challenge: * LLMs are dangerously useless for certain domains. * ... but can be quite useful for others. * The real problem is: They make it real tricky to tell, because most of all they are trained to sound professional and authoritative. They hallucinate papers because that's what authoritative answers look like. That already means I think LLMs are far less useful than they appear to be. It doesn't matter how amazing a technology is: If it has failure modes and it is very difficult to know what they are, it's dangerous technology no matter how awesome it is when it is working well. It's far simpler to deal with tech that has failure modes but you know about them / once things start failing it's easy to notice. Add to it the incessant hype, and, oh boy. I am not at all surprised that LLMs have a ridiculously wide range as to detractors/supporters. Supporters of it hype the everloving fuck out of it, and that hype can easily seem justified due to how LLMs can produce conversational, authoritative sounding answers that are explicitly designed to make your human brain go: Wow, this is a great answer! ... but experts read it and can see the problems there. Which lots of tech suffers from: as a random example: Plenty of highly upvoted apparently fantastically written Stack Overflow answers have problems. For example, it's a great answer... for 10 years ago; it is a bad idea today because the answer has been obsoleted. But between the fact that it's overhyped and particularly complex to determine an LLM answer is hallucinated drivel, it's logical to me that experts are hyperbolic when highlighting the problems. That's a natural reaction when you have a thing that SEEMS amazing but actually isn't.

fragmede 2y ago
> Stack Overflow answers have problems. For example, it's a great answer... for 10 years ago To be fair, that's a huge problem with stack overflow and its culture. A better version of stack overflow wouldn't have that particular issue.

dmichulke 2y ago

It says we don't have a lower bound on the effectiveness. It's (currently) like an ad saying "this product can improve your stuff up to 300%"

knowitnone 2y ago

If it makes data up, then it is worthless for all implementations. I'd rather it said I don't have info on this question.

joquarky 2y ago
> all implementations Are you speaking for yourself or everyone?
anamexis 2y ago
It only makes it worthless for implementations where you require data. There's a universe of LLM use cases that aren't asking ChatGPT to write a report or using it as a Google replacement.
- timacles 2y ago
  The problem is that yes llms are great when working on some regular thing for the first time. You can get started at a speed never before seen in the tech world. But as soon as your use case goes beyond that LLMs are almost useless. The main complaint that yes its extremely helpful in that specific subset of problems, it’s not actually pushing human knowledge forward. Nothing novel is being created with it. It has created this illusion of being extremely helpful when in reality it is a shallow kind of help.
deleted 2y ago
[deleted]
brookst 2y ago
Does “it” apply to Homo sapiens as well?
tasuki 2y ago
> If it makes data up, then it is worthless for all implementations. Not true. It's only worthless for the things you can't easily verify. If you have a test for a function and ask an LLM to generate the function, it's very easy to say whether it succeeded or not. In some cases, just being able to generate the function with the right types will mostly mean the LLM's solution is correct. Want a `List(Maybe a) -> Maybe(List(a))`? There's a very good chance a LLM will either write the right function or fail the type check.

camillomiller 2y ago

That software just didn‘t work that way. I don’t think it tried to convince the users that they were wrong by spouting nonsense that seems legitimate.

mywittyname 2y ago

It says that people need training on what the appropriate use-cases for LLMs are. This is not the type of report I'd use an LLM to generate. I'd use a database or spreadsheet. Blindly using and trusting LLMs is a massive minefield that users really don't take seriously. These mistakes are amusing, but eventually someone is going to use an LLM for something important and hallucinations are going to be deadly. Imagine a pilot or pharmacist using an LLM to make decisions. Some information needs to come from authoritative sources in an unmodified format.

michaelcampbell 2y ago

> And that says… what? The entire LLM technology is worthless for all applications, from all implementations? You're the first in the thread to have brought that up; there are far more charitable ways to have interpreted the post you're replying to.