5 ms·

I'm far from the first to make this observation but LLMs are like anti-compression algorithms when used like that, a simple idea gets expanded into a bloated me

I'm far from the first to make this observation but LLMs are like anti-compression algorithms when used like that, a simple idea gets expanded into a bloated mess by an LLM, then sent to someone else who runs it through another LLM to summarize it back to something approximating the original prompt. Nobody benefits aside from Sam Altman and co, who get to pocket a cool $0.000000001 for enabling this pointless exercise.

throwawaysleep 2y ago
Depends on what you are looking for. I’ve turned half baked ideas into white papers for plenty of praise. I’ve used them to make my Jira tickets seem complicated and complete. I’ve used them to get praised for writing comprehensive documentation. Part of my performance review is indirectly using bloat to seem sophisticated and thorough.
- generativenoise 2y ago
  Would be nice to fix the performance reviews so we don't end up in a arms race of creating bloat until it becomes so unproductive it kills the host. Over-fitting proxy measures is one of the scourges of modernity. The only silver lining is if it becomes so wide spread and easy it loses the value of seeming sophisticated and thorough.
  - FridgeSeal 2y ago
    > creating bloat until it becomes so unproductive it kills the host Maybe we should let/encourage this to happen. Maybe letting bloated zombie-like organisations bloat themselves to death would thin the herd somewhat, to make space for organisations that are less “broken”.
    - justinclift 2y ago
      "But at what price?" is probably the right question here, and that'd be a case by case basis thing. ;)
      - GreenWatermelon 2y ago
        All FAANG/MAGMA dying is a bonus. The cherry on top. Net positive for humanity. A best case scenario.
      - elzbardico 2y ago
        I am on the mind that every organization should eventually die before it becomes a monster. I am also not a huge fan of inheritance for the same reason.
- necovek 2y ago
  I fully believe you and I am saddened by the reality of your situation. At the same time, I strive really hard to influence the environment I am in so it does not value content bloat as a unit of productivity, so hopefully there are at least some places where people can have their sanity back!
- musicale 2y ago
  > comprehensive documentation Documentation is an interesting use case. There are various kinds of documentation (reference, tutorial, architecture, etc.) and LLMs might be useful for things like - repetitive formatting and summarization of APIs for reference - tutorials which repeat the same information verbosely in an additive, logical sequence (though probably a human would be better) - sample code (though human-written would probably be better) The tasks that I expect might work well involve repetitive reformatting, repetitive expansion, and reduction. I think they also might be useful for systems analysis, boiling down a large code base into various kinds of summaries and diagrams to describe data flow, computational structure, signaling, etc. Still, there is probably no substitute for a Caroline Rose[1] type tech writer who carefully thinks about each API call and uses that understanding to identify design flaws. [1] https://folklore.org/Inside_Macintosh.html?sort=date https://folklore.org/Inside_Macintosh.html?sort=date
  - chmod775 2y ago
    Yes, but none of the current LLMs are even remotely useful doing that kind of work for even something moderately complex. I have a 2k LOC project that no LLM even "understands" *. They can't grasp what it is: It's a mostly react-compatible implementation of "hooks" to be used for a non-DOM application. Every code assistant thinks it's a project using React. Any documentation they write at best re-states what is immediately obvious from the surrounding code (Useless: I need to explain why), or is some hallucination trying to pretend it's a React app. To their credit they've slowly gotten better now that a lot of documentation already exists, but that was me doing the work for them. What I needed them to do was understand the project from existing code, then write documentation for me. Though I guess once we're at the point AI is that good, we don't need to write any documentation anymore, since every dev can just generate it for themselves with their favorite AI and in the way they prefer to consume it. * They'll pretend they understand by re-stating what is written in the README, then proceed to produce nonsense.
    - justinclift 2y ago
      I've found "Claude 3.7 Sonnet (Thinking)" to be pretty good at moderately complex code bases, after going through the effort to get it to be thorough. Without that effort it's a useless sycophant and is functionally extremely lazy (ie takes short cuts all the time). Don't suppose you've tried that particular model, after getting it to be thorough?
- investa 2y ago
  [flagged]
- bdangubic 2y ago
  I’d rather be homeless in Philadelphia than work where you work
  - cwalv 2y ago
    This kind of "perf review" hacking works ~everywhere; how well it works correlates with how entrenched the organization is (i.e., how hard it is for new players to disrupt). You don't have to play the game the same way to work there. But it helps to accept that others will play it, and manage your own expectations accordingly.
    - bdangubic 2y ago
      But it helps to accept that others will play it Feel for you or anyone surrounded by such others but it is most definitely not everywhere - that is used to justify your presence in a place of work you should not be
    - palata 2y ago
      > This kind of "perf review" hacking works ~everywhere I don't have tons of examples, but in my experience: * This worked in toxic environments. They deserve it. * This doesn't work in a functional environment, because they don't have those bullshit metrics. If you have to rely on those tricks, it's time to look for another job.
      - seattle_spring 2y ago
        Which big, well-paying companies do not have "those bullshit metrics"? I know for a fact that Meta, Google, Stripe, Airbnb, and Oracle all lean heavily on performance review cycles based entirely on ridiculous metrics. Getting ahead there requires you to play the stupid games GP is suggesting.
        bdangubic 2y ago
        If you work there, as OP said, it's time to look for another job.
- Wowfunhappy 2y ago
  ...thinking about it, there are probably situations where making something more verbose makes it take less effort to read. I can see how an LLM might be useful in that situation.
- palata 2y ago
  If your organisation is such that you have to do this even though you are competent for your job, then they deserve it. They lose money because they do it wrong. If your organisation is functional and you are abusing it by doing that, then you deserve to get fired.
musicale 2y ago
> LLMs are like anti-compression algorithms when used like that, a simple idea gets expanded into a bloated mess by an LLM, I think that's the answer: LLMs are primarily useful for data and text translation and reduction, not for expansion. An exception is repetitive or boilerplate text or code where a verbose format is required to express a small amount of information.
- derefr 2y ago
  There is one other very useful form of "expansion" that LLMs do. If you aren't aware: (high-parameter-count) LLMs can be used pretty reliably to teach yourself things. LLM base models "know things" to about the same degree that the Internet itself "knows" those things. For well-understood topics — i.e. subjects where the Internet contains all sorts of open-source textbooks and treatments of the subject — LLMs really do "know their shit": they won't hallucinate, they will correct you when you're misunderstanding the subject, they will calibrate to your own degree of expertise on the subject, they will make valid analogies between domains, etc. Because of this, you can use an LLM as an infinitely-patient tutor, to learn-through-conversation any (again, well-understood) topic you want — and especially, to shore up any holes in your understanding. (I wouldn't recommend relying solely on the LLM — but I've found "ChatGPT in one tab, Wikipedia open in another, switching back and forth" to be a very useful learning mode.) See this much-longer rambling https://news.ycombinator.com/item?id=43797121 https://news.ycombinator.com/item?id=43797121 for details on why exactly this can be better (sometimes) than just reading one of those open-source textbooks.
  - deleted 2y ago
    [deleted]
  - jcul 2y ago
    Yeah you're totally right with this use case. It feels like the information is there strewn across the internet, in forums, Reddit posts, stack overflow, specs, books. But to trawl though it all was so time consuming. With an LLM you can quickly distill it down to just the information you need. Saying that, I do feel like reading the full spec for something is a valuable exercise. There may be unknown unknowns that you can't even ask the LLM about. I was able to become a subject expert in different fields just but sitting down and reading through the specs / RFCs, while other colleagues continued to struggle and guess.
charlieyu1 2y ago
I blame humans. I never understand why unnecessarily long writing is required in a lot of places.
- Aeolun 2y ago
  Rituals are significant because they are long. A ritual that consisted of the words “Rain please” wouldn’t convince the gods, much less their human followers.
- deleted 2y ago
  [deleted]
- necovek 2y ago
  "I have made this longer than usual because I have not had time to make it shorter." — attributed to many[1] The funny thing is that people use LLMs to do the opposite instead of what is implied to be a smarter thing to do with the above quote. [1] https://quoteinvestigator.com/2012/04/28/shorter-letter/ https://quoteinvestigator.com/2012/04/28/shorter-letter/
devnullbrain 2y ago
Yep. They're very closely linked. http://prize.hutter1.net/ http://prize.hutter1.net/ Note the preamble, FAQs, and that all of the winning entries are now neural networks.
jameshart 2y ago
Actually, pretty sure Sam Altman gets to spend that money on power and compute, not sure they’ve figured out how to turn it into an income stream yet.
arealaccount 2y ago
I think they actually lose the $0.000001

throwawaysleep 2y ago

Depends on what you are looking for. I’ve turned half baked ideas into white papers for plenty of praise. I’ve used them to make my Jira tickets seem complicated and complete. I’ve used them to get praised for writing comprehensive documentation. Part of my performance review is indirectly using bloat to seem sophisticated and thorough.

generativenoise 2y ago
Would be nice to fix the performance reviews so we don't end up in a arms race of creating bloat until it becomes so unproductive it kills the host. Over-fitting proxy measures is one of the scourges of modernity. The only silver lining is if it becomes so wide spread and easy it loses the value of seeming sophisticated and thorough.
- FridgeSeal 2y ago
  > creating bloat until it becomes so unproductive it kills the host Maybe we should let/encourage this to happen. Maybe letting bloated zombie-like organisations bloat themselves to death would thin the herd somewhat, to make space for organisations that are less “broken”.
  - justinclift 2y ago
    "But at what price?" is probably the right question here, and that'd be a case by case basis thing. ;)
    - GreenWatermelon 2y ago
      All FAANG/MAGMA dying is a bonus. The cherry on top. Net positive for humanity. A best case scenario.
    - elzbardico 2y ago
      I am on the mind that every organization should eventually die before it becomes a monster. I am also not a huge fan of inheritance for the same reason.
necovek 2y ago
I fully believe you and I am saddened by the reality of your situation. At the same time, I strive really hard to influence the environment I am in so it does not value content bloat as a unit of productivity, so hopefully there are at least some places where people can have their sanity back!
musicale 2y ago
> comprehensive documentation Documentation is an interesting use case. There are various kinds of documentation (reference, tutorial, architecture, etc.) and LLMs might be useful for things like - repetitive formatting and summarization of APIs for reference - tutorials which repeat the same information verbosely in an additive, logical sequence (though probably a human would be better) - sample code (though human-written would probably be better) The tasks that I expect might work well involve repetitive reformatting, repetitive expansion, and reduction. I think they also might be useful for systems analysis, boiling down a large code base into various kinds of summaries and diagrams to describe data flow, computational structure, signaling, etc. Still, there is probably no substitute for a Caroline Rose[1] type tech writer who carefully thinks about each API call and uses that understanding to identify design flaws. [1] https://folklore.org/Inside_Macintosh.html?sort=date https://folklore.org/Inside_Macintosh.html?sort=date
- chmod775 2y ago
  Yes, but none of the current LLMs are even remotely useful doing that kind of work for even something moderately complex. I have a 2k LOC project that no LLM even "understands" *. They can't grasp what it is: It's a mostly react-compatible implementation of "hooks" to be used for a non-DOM application. Every code assistant thinks it's a project using React. Any documentation they write at best re-states what is immediately obvious from the surrounding code (Useless: I need to explain why), or is some hallucination trying to pretend it's a React app. To their credit they've slowly gotten better now that a lot of documentation already exists, but that was me doing the work for them. What I needed them to do was understand the project from existing code, then write documentation for me. Though I guess once we're at the point AI is that good, we don't need to write any documentation anymore, since every dev can just generate it for themselves with their favorite AI and in the way they prefer to consume it. * They'll pretend they understand by re-stating what is written in the README, then proceed to produce nonsense.
  - justinclift 2y ago
    I've found "Claude 3.7 Sonnet (Thinking)" to be pretty good at moderately complex code bases, after going through the effort to get it to be thorough. Without that effort it's a useless sycophant and is functionally extremely lazy (ie takes short cuts all the time). Don't suppose you've tried that particular model, after getting it to be thorough?
investa 2y ago
[flagged]
bdangubic 2y ago
I’d rather be homeless in Philadelphia than work where you work
- cwalv 2y ago
  This kind of "perf review" hacking works ~everywhere; how well it works correlates with how entrenched the organization is (i.e., how hard it is for new players to disrupt). You don't have to play the game the same way to work there. But it helps to accept that others will play it, and manage your own expectations accordingly.
  - bdangubic 2y ago
    But it helps to accept that others will play it Feel for you or anyone surrounded by such others but it is most definitely not everywhere - that is used to justify your presence in a place of work you should not be
  - palata 2y ago
    > This kind of "perf review" hacking works ~everywhere I don't have tons of examples, but in my experience: * This worked in toxic environments. They deserve it. * This doesn't work in a functional environment, because they don't have those bullshit metrics. If you have to rely on those tricks, it's time to look for another job.
    - seattle_spring 2y ago
      Which big, well-paying companies do not have "those bullshit metrics"? I know for a fact that Meta, Google, Stripe, Airbnb, and Oracle all lean heavily on performance review cycles based entirely on ridiculous metrics. Getting ahead there requires you to play the stupid games GP is suggesting.
      - bdangubic 2y ago
        If you work there, as OP said, it's time to look for another job.
Wowfunhappy 2y ago
...thinking about it, there are probably situations where making something more verbose makes it take less effort to read. I can see how an LLM might be useful in that situation.
palata 2y ago
If your organisation is such that you have to do this even though you are competent for your job, then they deserve it. They lose money because they do it wrong. If your organisation is functional and you are abusing it by doing that, then you deserve to get fired.

musicale 2y ago

> LLMs are like anti-compression algorithms when used like that, a simple idea gets expanded into a bloated mess by an LLM, I think that's the answer: LLMs are primarily useful for data and text translation and reduction, not for expansion. An exception is repetitive or boilerplate text or code where a verbose format is required to express a small amount of information.

derefr 2y ago
There is one other very useful form of "expansion" that LLMs do. If you aren't aware: (high-parameter-count) LLMs can be used pretty reliably to teach yourself things. LLM base models "know things" to about the same degree that the Internet itself "knows" those things. For well-understood topics — i.e. subjects where the Internet contains all sorts of open-source textbooks and treatments of the subject — LLMs really do "know their shit": they won't hallucinate, they will correct you when you're misunderstanding the subject, they will calibrate to your own degree of expertise on the subject, they will make valid analogies between domains, etc. Because of this, you can use an LLM as an infinitely-patient tutor, to learn-through-conversation any (again, well-understood) topic you want — and especially, to shore up any holes in your understanding. (I wouldn't recommend relying solely on the LLM — but I've found "ChatGPT in one tab, Wikipedia open in another, switching back and forth" to be a very useful learning mode.) See this much-longer rambling https://news.ycombinator.com/item?id=43797121 https://news.ycombinator.com/item?id=43797121 for details on why exactly this can be better (sometimes) than just reading one of those open-source textbooks.
- deleted 2y ago
  [deleted]
- jcul 2y ago
  Yeah you're totally right with this use case. It feels like the information is there strewn across the internet, in forums, Reddit posts, stack overflow, specs, books. But to trawl though it all was so time consuming. With an LLM you can quickly distill it down to just the information you need. Saying that, I do feel like reading the full spec for something is a valuable exercise. There may be unknown unknowns that you can't even ask the LLM about. I was able to become a subject expert in different fields just but sitting down and reading through the specs / RFCs, while other colleagues continued to struggle and guess.

charlieyu1 2y ago

I blame humans. I never understand why unnecessarily long writing is required in a lot of places.

Aeolun 2y ago
Rituals are significant because they are long. A ritual that consisted of the words “Rain please” wouldn’t convince the gods, much less their human followers.
deleted 2y ago
[deleted]
necovek 2y ago
"I have made this longer than usual because I have not had time to make it shorter." — attributed to many[1] The funny thing is that people use LLMs to do the opposite instead of what is implied to be a smarter thing to do with the above quote. [1] https://quoteinvestigator.com/2012/04/28/shorter-letter/ https://quoteinvestigator.com/2012/04/28/shorter-letter/

devnullbrain 2y ago

Yep. They're very closely linked. http://prize.hutter1.net/ http://prize.hutter1.net/ Note the preamble, FAQs, and that all of the winning entries are now neural networks.

jameshart 2y ago

Actually, pretty sure Sam Altman gets to spend that money on power and compute, not sure they’ve figured out how to turn it into an income stream yet.

arealaccount 2y ago

I think they actually lose the $0.000001